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![International Journal of Computer Science and Business Informatics
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ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 1
Determination of the Account
Personal Data Adequacy of Web-
Community Member
Solomia Fedushko, Yuriy Syerov, Andriy Peleschyshyn and Korzh
Roman
Social Communications and Information Activities Department,
L'viv Polytechnic National University,
Ukraine, L'viv, S. Bandera Street 12
ABSTRACT
This article considers the current problem of investigation and development of data
verification of virtual community member by means of computer-linguistic analysis of
web-members socio-demographic profiles for web-community member identification. The
algorithm of formation system of lingvo-communicative indicators based the training
selection of web-forum members is designed. This algorithm includes the formation of
matrix of linguistic-communicative indicators and lingvo-communicative indicator weight
coefficient determination. The computer-linguistic analysis of web-community members'
information tracks is realized and verification of lingvo-communicative indicators of
gender, age and sphere of activities of web-community member is established. Based on
these results of the investigation the software algorithm of web-community members'
socio-demographic profiles verification is designed and software "Verifier of the socio-
demographic profile" is exploited. The account personal data adequacy of web-community
member is determined by means of computation of the measure of the adequacy of personal
account data. The calculation method of reliability of the result of the socio-demographic
characteristics verification of web-community member is developed for constructing the
socio-demographic profile of the web-member for web-community management.
Keywords
Socio-demographic profile, Software, Marker, Web-community member, Personal data,
Validation.
1. INTRODUCTION
The most important issues of web-communities content analysis today is
analysis of web-users’ personal data [1, 2]. In spite of significant importance
for the further development of this research field, methods of analysis are
undeveloped in particular personal information on account of web-
communities’ users. Development of web-community management software
is a priority issue because the web-community is a popular and mass service
at WWW, and existing software management tools are imperfect and not
integrated. Authenticity of web-community user personal data is an
important thing in the successful managing of web-communities.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-3-320.jpg)
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The scientific task of validation method development for web-communities
members’ personal data, including their socio-demographic characteristics,
based on computer-linguistic analysis of the informational content is the
current area of the research in computer linguistics. Since without linguistic
methods and computer-aided tools this is the hardest task and requires
significant time spending for web-communities administrators.
2. BACKGROUND STUDY
The verification of personal data that is contained in the global system
WWW is relevant and important research object in the following areas:
Assessment of the online information reliability.
The concept of content reliability, content relevance and reliability
of highly specialized content.
The formal review of perception of trust in the information among
regular Internet.
The personal data reliability and quality.
Verification of socio-demographic users’ characteristics in WWW.
The results of the research in the last scientific direction – of socio-
demographic characteristics verification of users of the global environment
WWW [3, 4] – are in demand of a wide range of experts in the organization
and operation of web-communities, as such, that should ensure their
performance and efficiency. This raises an important problem of the new
methods and tools development that would have a proper scientific
justification, formality, predictable performance and versatility for
analyzing the socio-demographic characteristics reliability of the web-
communities members.
Socio-demographic characteristics
Age
Adult
Teenager
Natural
sciences
Formal
science
Gender
Man
Woman
Education level
Low
educated
Highly
educated
Sufficiently
educated
Sphere of activity
Social
sciences
Figure 1. The structure studied by social-demographic characteristics of a web-user](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-4-320.jpg)
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For web-community user data validation, in order to improve web-
communities management [5] and to improve target techniques in online
advertising [6] is enough to analyze such basic socio-demographic
characteristics (see. Figure 1).
2.1 The reasons of socio-demographic characteristics validation:
Obtaining data from real users of social networking pages ("Facebook",
"Twitter", "Habrahabr", "Google+", etc.), the popular online newspapers
and magazines, dating sites ("LoveUA", "FindLove.in.UA", “12 Kisses”,
“Dating foreigners website”) and web-forums (Ukrainian forum of
programmers “Replace.Org.Ua”, “Domivka.Net: Ukrainian Forum”, “The
first site of the Ukrainian community in Italy”) is urgent task for web-
community administrators, police, private detectives (services that have
been increasingly needed by users of global environment Internet) and
individual user of any information resource.
Verification and setting of web-users’ personal data who performs illegal
actions that are offensive to opponents from psychological, financial, legal
angle, in particular, who levies blackmail, sends hate mails, spreads false
and aspersion information and conduct other electronic bullying.
2.1.1 Age
Age category is chosen for specified age validation in web-community
member due to a number of important factors: the presence of real online
threats to Internet users with the age of 6 to 17 years (these include
disclosure of personal confidential information, access to content that do not
meet age peculiarities and adversely affect the physical and mental health of
the child, online abuse, internet marketing crimes, etc.) and the need for
screening age group of children who have applied or already are web-
community member, that is intended only for adult web-space users.
The characteristic features of a web-identity are self-expression and
experimentation with the aim to make a definite impression on the users of
the web-community and this is peculiar especially to growing age.
The problem of age differentiation is that the penetration rate of children is
increasing in web-communities, which are intended for adult users'
communication, and this destroys communicative atmosphere of community
and vice versa, children are increasingly claiming to be adult members. This
situation can lead community administrator to criminal charges [7]. An
example of web-communities for teenagers online communication is:
"Student Forum|UNIVER-SITY", "chat for teens", chat "teenager", "chat for
teens", "Just chat" and for adults "Our anecdote with Pepper" and others.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-5-320.jpg)
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2.1.2 Education
Many community administrators require web-community members to
follow certain conventions of web-communication. Web-communication
convention depends on the objective goal and projected scenarios of the
web-community owners. An important factor in the possibility of
participating in a web-community is a high literacy level of web-community
member [8], level of higher education and skills.
The method of screening illiteracy and with low education level web-
community member will significantly reduce the time and financial costs,
and managers' efforts to moderate web-community. In order to screen
illiterate web- member it required to classify all members by the level of
literacy, which will help to determine the likely level of each web-
community member education. In the task automation research of detecting
errors in the text are only considered character errors. Error analysis and
data consolidation that were conducted by scientists, allows us to offer the
errors typology and to classify members in the order of education level.
2.1.3 Scope of activity
A web-member in a greater or lesser degree can belong to several areas of
interest, as the impact of the content creation in web-communities serve a
direction of education, professional activity and range of interests in spare
time. However, the result of the analysis is to determine the scope of activity
of web-community member. In the general scope of activities are classified
as science fields in the following areas: Natural sciences; social sciences;
formal science. This division is based on analysis of web-community
members Internet communication with different scopes of activities.
In web-community moderation that is intended for communication between
members of certain areas, there many questions appear about level of
professionalism, ethical principles, so filtering of web-users by scope of
activities is a necessary and important task of community administration
(government and policy portals) to improve the web-community position.
2.1.4 Gender
In order to avoid gender conflicts in web-communities that are intended for
women (L'viv Women's Forum “Cult of Beauty”, "Girls chat", Forum
"L'viv-mama" et al.) and for men ("Man Forum", "Anti-feminine site" etc.)
administrators of these communities need to enter a strict gender division.
"Web-gender change", that is a web-user creation identity of the opposite
sex, it is common on the Internet and is caused by the following factors as
the impact of cultural gender stereotypes, expression of homosexual
tendencies or transsexual or diffuse gender identity. So-called web-sex
change is more peculiar to men due to several reasons desire to control and
manipulate others, for women it is easier to get help and attract attention,](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-6-320.jpg)
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8. REFERENCES
[1] Fedushko, S., Syerov, Yu., 2013. Design of registration and validation algorithm of
member’s personal data, International Journal of Informatics and Communication
Technology, Vol.2, No.2, pp. 93-98.
[2] Shakhovska, N., 2011. Methods of customer data processing using intelligent agent of
data sources structure determination. Actual Problems of Economics, Vol. 7(120),
pp. 338-346.
[3] Fedushko, S., Peleschyshyn, O., Peleschyshyn, A., Syerov, Yu., 2013. The verification
of web-community member's socio-demographic characteristics profile, Advanced
Computing: An International Journal, Vol.4, No.3, pp. 29-38.
[4] Syerov, Yu., Peleschyshyn, A., and Fedushko, S., 2013. The computer-linguistic
analysis of socio-demographic profile of web-community member. International
Journal of Computer Science and Business Informatics, Vol. 4, No. 1, pp. 1-13.
[5] Shakhovska, N. and Syerov, Yu., 2009. Web-community ontological representation
using intelligent dataspace analyzing agent. X-th International Conference "The
Experience of Designing and Application of CAD Systems in Microeletronics",
Polyana-Svaliava, Ukraine, pp. 479–480.
[6] Shakhovska, N., 2011. Consolidated processing for differential information products.
VII-th International Conference "Perspective Technologies and Methods in MEMS
Design", Polyana-Lviv, Ukraine, p. 176.
[7] Fedushko, S., Bardyn, N., 2013. Algorithm of the cyber criminals identification.
Global Journal of Engineering, Design & Technology, Vol. 2, No. 4, pp. 56-62.
[8] Korzh, R., Peleschyshyn, A., Syerov, Yu., and Fedushko, S., 2014. The cataloging of
virtual communities of educational thematic. Webology, 11(1), pp. 1-16.
This paper may be cited as:
Fedushko, S., Syerov, Y., Peleschyshyn, A. and Roman, K., 2015.
Determination of the Account Personal Data Adequacy of Web-Community
Member. International Journal of Computer Science and Business
Informatics, Vol. 15, No. 1, pp. 1-12.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-14-320.jpg)
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staff and the system is required to achieve network protection against
attacks [1]. As different staff members have different responsibilities,
different roles should be assigned to them when building the secure
network. To provide a secure network design, an analysis of possible threats
should be carried out. Appropriate risk analysis can provide an outlook on
possible network threats, network vulnerabilities and the best mechanisms
to maintain and mitigate these effects. Different security mechanisms can be
implemented to secure any organization’s network beginning from the core
network and ending with securing user end point. However, some
vulnerable point could be missed which can easily provide a base to attack
the network. Well-designed security system can guarantee high security
level which is required especially in protecting data. The essential approach
towards high level network security is layered defense.
Layered defense is defined as the concept of protecting a computer network
with a series of defensive mechanisms such that if one mechanism fails,
another will already be in place to thwart an attack [2]. Because of the
variety of attacks, no single technique can successfully protect the network.
By Utilizing layered defense strategy [1], any attack can be prevented or at
least detected. This approach requires deep coordinates between users and
network resources in order to assure secure data exchange. Rather than
dropping few firewalls between network or installing additional malware
detection software, layered defense implementing multiple strategies which
are divided into different layers. Each layer introduce partial defense
technique against specific attack, once the layer defense is passed, next layer
defense should be able to mitigate the attack or at least detect it. Like any
other security system design, layered security requires a deep analysis of the
attacks in order to identify which mechanisms to employ and where. Figure
1 shows the basic steps to design a security system. In this paper, we
introduce layered defense approach to provide total network protection. The
paper is organized as follows: section 2 explains the most famous attack on
computer networks, in section 3, we discuss the importance of risk analysis
in building network security system. Section 4 introduces detailed layered
defense approach, finally section 5 contains the conclusion on our work.
Figure 1: security design steps.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-16-320.jpg)
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2. ATTACK CLASSIFICATION
The common known attacks can be classified as follows [3, 4]:
A. Eavesdropping or packet sniffing
In this case the attacker captures each packet flows across the network with
the aid of packet sniffer application program. Without strong encryption, the
captured packed is plain text which simply reveal networks information [5].
B. Data modification
The attacker aims to modify the content of the captured packet without the
knowledge of the sender or the receiver.
C. IP address spoofing
This attack enables the attacker to access network data, modify it or even
delete it [5, 6].
D. Password based attacks
Once the attacker discloses the user’s password, he can access user’s data
and has all the rights and privileges as real user.
All previous attacks will result in some data being stolen or modified,
anyway the network can continue work properly. When the attacker is more
violent, it will develop more dangerous attacks which will lead not only to
network data changed, but also to destroy the network and bring it down [6].
Once the attacker captured any network node, the node is said to be
compromised. In this case the attacker can start a second group of network
attacks which contains:
A. Trust exploitation
As devices in the shared environment should trust the information from each
other, an attacker can use the compromised device to send and modify
information as a trusted user.
B. Port redirection
By installing port redirection software like NetCat on the compromised
device, the attacker can redirect packets to another port. In this case, all
network data including IP addresses, passwords and other important
information can be monitored by the attacker.
C. Man in the middle attack
In this attack, all packets exchanged between two users is passed through
the compromised device. The attacker could modify the packets without
being noticed by the sender or receiver.
D. Denial of service](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-17-320.jpg)
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By flooding the network with extra traffic, the attacker aims to prevent the
network from performing its job. For example, the attacker can flood the
server with so many requests which makes it take a long time to process
these request and become unavailable for other users. DoS attacks are the
hardest attacks to mitigate as they are performed using the allowed traffic in
the network [7].
E. Malicious software (Viruses, worms and Trojans)
Once the attacker becomes trusted within the network, he can send packets
contains viruses, worms and Trojans to different network devices which will
deal with the data as trusted data. These malware can affect devices in
different ways, starting from erasing files to run arbitrary codes causing
memory overloading, consequently switch of the device.
F. Network partitioning
Using port redirection attack and packet sniffing, the attacker can redirect all
the packets to flow to certain device which is basically compromised. In this
case, a lot of network nodes (devices) will be virtually out of the network,
which can a virtual network partitioning.
3. RISK ANALYSIS
The first step towards building a secure network, is to carefully identify and
analyze each attack and evaluate the risks introduced to the organization's
network by these attacks. Risk analysis helps to define possible damage
caused by the attacker and methods to mitigate this damage or even prevent
it. The basic methodology of risk analysis can be summarized as in [8]
Identify the assets.
Identify the threats.
Identify the vulnerabilities.
Identify the existing controls
Generally, previous four points can be seen as three short questions; what to
protect, from whom and how. Assets identification should be done first in
order to define what asset to protect. Network asset contains both hardware
and software components. Risk analysis should clearly define which asset to
be protected and what level of protection required. After that, the
organization should define the possible threats to its network. Threats
contains every unwanted events that can damage the assets, and can be
triggered by natural or human action. Identification of threat sources also is
important point, threat sources varies from natural, human or environmental
hence, good identification of threat source should be done even before
building the network architecture. Network vulnerabilities can be defined
as” a flaw or weakness in system security procedures, design,
implementation, or internal controls that could be accidentally triggered or](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-18-320.jpg)
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intentionally exploited and result in a security breach or a violation of the
system's security policy” [9]. The vulnerable points in the network will not
cause any harm unless some threat exploit to it. All vulnerabilities should be
well identified and monitored to detect any threat possibilities. The final
stage in risk analysis is to identify the existing controls. Controls mean all
existing procedures and mechanisms to mitigate the vulnerabilities. Existing
controls can be identified with the help of documentation of controls and
plans of risk treatment implementation. Multiple controls should be
assigned to mitigate every vulnerability, if one control failed, a
complimentary controls should be addressed to mitigate the threat.
Risk analysis can be done in two ways: Quantitative and qualitative [8].
Quantitative risk analysis is used to define the probability of risk occurrence
and possible losses, and assign them numerical values. Quantitative analysis
helps to estimate the assets, build cost, protect cost and repair cost.
Qualitative analysis is used to predict the level of protection required to the
network including asset and applications. Qualitative analysis represents the
initial monitoring to identify risks and threats that need deeper analysis, and
if the numerical threat estimation is required.
4. LAYERED DEFENSE APPROACH
Layered defense is defined as a set of network defense procedures and
technologies which aims to protect the network from intruders, these
techniques is organized such that if one failed to protect, the next one will
be ready to replace it. The complexity of the procedures depends on
organization requirements in terms of security level, cost and operability.
Any network security approach should be designed according to the
organization’s security policies which is defined as “a formal statement of
the rules by which people who are given access to an organization’s
technology and information assets must abide” [10]. In order to design a
secure network, it is really important to have a strong security policies. The
first step in security policies is to inform the network users how to protect
information and technology assets. Dividing people between network
administrators and users can help to protect the network by definition of
limited access. Also setting passwords for certain devices, information or
application will effectively protect the data from unwanted access. In
general, security policies can be summarized as: what to protect, why, from
whom and who is responsible for this protection procedure [11].](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-19-320.jpg)
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good configured perimeter. As firewall is the security guard which controls
the entry points of the network by checking every incoming and outgoing
packet, a set of rules should be predefined by the organization to help
configure the firewall properly. In this case, well configured firewall will be
able to decide what packets to accept and what to discard. According to [12]
two categories of firewalls exist; state-less firewalls and state-full. If the
firewall tested the fate of the packet by examine the packet itself, then it is
called state-less. But if the decision is made not only based on the packet
test but also by looking to the previous accepted packets, then it is called
state-full. As the packet flow is controlled, many harmful effects can be
eliminated keeping the network safe.
B. Core network defense
The basic key for core network protection is the good designed architecture.
DMZ which is network area separating between firewall and the first router
in the network is an important defense tool. DMZ hardware is working as
the second check point for the packets, by fragmenting the packet, DMZ can
detect whether the payload is malicious or not. Figure 3 illustrate the
implementation of the DMZ within the core network.
Intrusion detection and prevention systems IDPS forms the second defense
line in securing the core network. By collecting information from different
network sources, these systems can detect possible threats [13]. For
example, when the attacker performs port redirection attack, most of the
Figure 3: DMZ implementation to protect the core network](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-21-320.jpg)
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data flows to the compromised device. By analyzing the traffic in the
network, IDPS can find the threat and report to the system administrator to
take proper reaction. The secondary router in the system is also involved in
the layered protection [14]. By dividing the network into different working
groups (VPNs), the secondary router can disseminate the network traffic in
to proper working groups.
C. End point defense
The end point in the network could be both user’s device and servers.
User’s information can be protected by the mean of operating system
protection by adjusting security configurations. Other procedures could be
useful too such as closing unused ports, hard disk encryption and
application whitelisting. Host intrusion detection systems is also can be used
to protect hosts from outside attacks. Anti-viruses software protects the
device from malicious software. These software manages databases which
contain signature for all known malicious computer codes and use signature
scanning to define malicious files. By detecting these file, many attacks and
threats can be omitted.
D. Application defense
Many attacks target the applications especially those which run on the
server. Some of these attacks are; buffer overflow attacks, password
guessing attacks, directory traversal attacks, and poorly configured network
applications that expose data to unauthorized users. Most client applications
do not listen to network ports, so they usually are not susceptible to remote
network attacks. Different tools and solutions could be used to protect
applications like Internet Information Services hardening and SQL
hardening for protecting servers [15], also installing applications and their
updates should be done from their original vendors.
E. Data defense
As business data is the most valuable content of any organization, providing
data protection is the main goal for any network security system. Adding to
previous mechanics, data defense could be done by controlling the access to
files and folders using access control lists (ACLs) [16], besides using some
encryption techniques. To prevent data loss, data back up or restore should
be done periodically using CDs or external hard disk. Finally saving data on
external hard disks rather than keeping it on desktop device can also protect
it from being stolen.
Generally, the layered defense approach use multiple techniques together to
provide total security. For example; an attacker who has physical access to
the network’s computer has to gain authorization to access the data. As the
access is protected by user’s password, the attacker should gain this
password first. Once the attacker break first defense layer (the password),](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-22-320.jpg)
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second defense layer – in this case, it could be hard disk encryption- will be
ready to defend the attack. If the attacker succeed to break the encryption,
next defense layer – let’s say; host based intrusion detection system (IDS) -
can detect the attack, by comparing attacker behavior with system logs. The
intrusion detection system will report the attack to the administrator to take
the proper reaction.
5. CONCLUDING REMARKS
In this paper, we introduced a layered approach for computer network
security. The layered network defense can provide better security level by
the mean of arranging defense mechanism in consecutive layers such that
each mechanism has less attacks to deal with compared with the mechanism
in previous layer. Different security mechanisms are required to be
implemented in order to provide total network protection which increase the
cost and complexity of security system. Anyway, a good risk analysis of the
organization network can reduce the cost of implemented security
mechanisms by predicting which mechanism to apply and at which layer.
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Modeling of Citizen Claims
Processing by Means of Queuing
System
Oleksandr Markovets and Andriy Peleschychyn
Social Communications and Information Activity Department,
L'viv Polytechnic National University, Ukraine, L'viv, 12 Bandera Str.
ABSTRACT
This article considers the work of the system “Electronic Reception” as the queuing system.
An overview the structure of the system “Electronic Reception” as a chart is given. The
initial descriptions for the queuing system are formed. Also scheme simulation model of
“Electronic Reception” is represented and found probabilities of states of the system using
the application of queuing theory. Context diagram of process of queuing system
“Electronic Reception” is designed. Data flow diagrams of the first level of the queuing
system “Electronic Reception” and data flow diagram of the subsystem “Analysis of claim”
which detailed the context diagram of process of queuing system “Electronic Reception” is
designed. A simulation model of single-channel service system “Electronic Reception” is
realized. The initial output characteristics of a service system “Electronic Reception” and
the parameters of the simulation model are formed. The state probabilities of the service
system are found. For a description of the mathematical model queuing system “Electronic
Reception” use data that were obtained in one of the experiments.
Keywords
Queuing system; Simulation model; States marginal probability; Consolidation; Electronic
Reception; System.
1. INTRODUCTION
Under the modern conditions of information technologies development,
increases the role of the Internet in people's lives has emerged the concept of
"information society". Therefore there is a necessity to implement electronic
governance for communication between authorities and citizens in various
spheres of life.
One example of such contact is the implementation of electronic public
receptions. The main purpose of electronic receptions is providing the
citizens with passive and active access to public information, electronic
consulting, collecting and analyzing citizens' views about current events,
issues. Informational services, provided by electronic reception, include:
receiving electronic claims and offering electronic consultation, receiving
claims which are addressed directly to the heads of departments of the city
council [1].](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-38-320.jpg)
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The advantages of implementing electronic receptions in the field of
electronic governance are:
• ensure transparency of information by public authorities (citizen can
track their claims at all stages of consideration);
• citizens save time (you can get consultation through the Internet and
personal computer at home);
• access to resources at any time;
• saving privacy of citizens.
Despite listed above advantages, still remain some disadvantages:
• the processing time is unknown;
• because of large number of claims, some can be lost and not
considered;
• the time it takes to review an claim, may exceed the time limits
specified in the notice of consideration of claims and therefore
claims may remain unanswered.
In this case, in order to assess the performance of electronic receiving and, if
necessary, to make it more efficient, it is necessary to analyze it as a
queuing system.
It is necessary to solve a number of problems that may arise in the queuing
system. The main reason of these problems is irregular income of claims. It
is not possible to predict how and when complaints will be received by the
queuing system "Electronic Reception", and so there can be cases when the
system may not cope with incoming applications. There is a negative state
of system when system is almost always in a state of inaction. In such case,
the cost of its implementation is not justified [2].
It is important to organize the system to increase its throughput and
minimize losses of claims. On this depends on the number of channels that
are working on stream of claims, their productivity and discipline service.
Therefore it is important to analyze the work of the "Electronic Reception"
in artificially created conditions to obtain empirical results for the proper
relationship of government with citizens and quick respond.
2. THE ACTUALITY OF THE RESEARCH
The current planning problem of department activities in processing appeals
of citizens is quality determination of the department workload elaboration
and possibility to process the appropriate number of electronic appeals by
managers. Analytically can be defined only a part of performance indicators
of these departments. The basic indicator that characterized work quality of
the department is number of electronic appeals that are not elaborated in due
time, so-called overdue appeal. In existing system, the pendency time of](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-39-320.jpg)
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electronic appeal from the receipt time is impossible to determine by
mathematical means. Despite this requirement using simulation modeling is
obvious and undeniable. To construct the imitation model it is necessary to
reproduce as accurately as possible all the processes that occur in the
system. This requires analyzing in detail all system components and the
relationships between these components.
Established simulation model of system of electronic processing of appeals
applied and successfully used in the field of e-governance, particularly in
city councils that in improved service delivery to the city citizens are
interested. Also, this model is used in the educational organizations in order
to establish feedback to applicants, students, teachers, and, in general,
institutions, organizations and companies to establish regular contact with
its customers and to receive quickly respond to the proposals, complaints or
shortcomings in the work.
3. MODELING OF FUNCTIONING PROCESS OF QUEUING
SYSTEM "ELECTRONIC RECEPTION"
The article is supposed to explore applying queuing systems in claims
processing with the aim to consolidate information. Thus, there will be
description of processes that occur in the "Electronic Reception",
formulation of baseline characteristics of the structure of the queuing system
and found marginal probabilities of states based on the results of simulation
[3]. To represent the system of electronic reception and further define
primary characteristics of the queuing system, it is necessary to build data
flow diagram, which will show the major stages of the processing of
citizens’ claims in the system.
Queuing system
"Electronic
reception" new claims
processed claims Departments
of the City
Council
Users
claims
reply
Figure 1. Context diagram
Contextual diagram shows two external entities, which queuing system
"Electronic reception" interacts with. The first external entity represents
citizens who are users and source of claims in the system. The second
external essence denotes structural units (departments of the City Council).
They are receiving citizens’ claims coming from email reception, and after
processing requests, send a reply back to the email reception.
The diagram is further detailized to trace the claim from its ingress in
electronic reception to the end of consideration process, in other words, to
the moment when the users receive an response email.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-40-320.jpg)
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in the citizens` claims of three types: application of the relative priority
(claim1), application of conventional type (claim2) and processed claim that
only requires an answer (claim3). An arrival time of application is
determined by the exponential distribution law. The service time is given to
implement the system with priority, but it is believed to be exponentially
distributed [4].
Only one claim is served by a channel at a time period. If the channel is not
loaded when a message comes, claim will be processed. If there are no
claims, the system is idle.
The discipline of service is following: if the system is already analyzing an
ordinary claim or a processed claim, the claim with priority does not
displace the claim of these types of services, and becomes the next.
If the system has no claim with priority, claims are served according to the
FIFO discipline. If the system has several claims with priority, they are
ordered for processing adhering to the rules of the discipline FIFO
discipline.
Basing on the described above initial output characteristics perform, the
simulation model is constructed and common parameters to the system as a
whole and blocks separately are formed. As a result of simulation and
analysis of the results is proved that the number of service channels,
necessary for the simplest flows manages flows and other types processing.
FIFO
path combiner
(setting
priorities)
Exponentially
distribution
Exponentially
distribution
Exponentially
distribution
answeranswer
Claim 1Claim 1
Claim 2Claim 2
Claim 3Claim 3
uniform
distribution
Figure 5. A simulation model of single-channel service system "Electronic receiver»
5. FINDING STATE PROBABILITIES OF THE SERVICE SYSTEM
This chapter is based on data obtained through simulation, we use the
formulas of the applications of the theory of service system to describe the](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-44-320.jpg)
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7. REFERENCES
[1] Serenok, A., 2011. Introduction of technologies of e-government in activity of organs
of local self-government, Journal of Kharkiv Regional Institute of Public
Administration of the National Academy of Public Administration, No. 1.
[2] Markovets, O., Peleshchyshyn, A., Zhezhnych, P., 2011. Designing a system
processing appeals to local authorities, Computer Science and Information
Technology: Proceedings of the National University "Lviv Polytechnic", No.694,
pp. 153-160.
[3] Markovets, O., 2011. A mathematical model for the applicant of e-government,
Information Systems and Networks: Proceedings of the National University
"Lviv Polytechnic", No. 699, pp.154-163.
[4] Anikovskiy, V., Erofeeva, L., Novgorod, N., 2010. Elements of queuing theory. Basic
concepts. Tasks. Guide to solving problems, Novosibirsk State Technical University.
This paper may be cited as:
Markovets O. and Peleschychyn A., 2015. Modeling of Citizen Claims
Processing by Means of Queuing System. International Journal of
Computer Science and Business Informatics, Vol. 15, No. 1, pp. 36-46.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-48-320.jpg)
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goals, that either don`t correspond to their interests or contain information
risks to an individual, society or state.
Thus, there exist not only beneficial to society virtual communities aiming
at enhancing society`s well-being as a whole, or separate social groups and
individuals life, however social networks are more and more used for
creating destructive virtual communities. Destructive communities do not
exclude illegal methods from their strategies. They direct their aggression at
opposing social networks or generally at society.
One of the methods used in information wars and preventing information
hazards is informational influence, which is employed for informational
management. In this case informational management means providing the
objects of influence with the information that will make them alter the
course of their behavior.
Informational influence success to the great extent depends on the right
choice of the object for informational influence. To put it differently
information advantage is essential. This necessity is a result of the
complicated discussion structure of virtual communities. Due to the
immense network of interconnected with hyperlinks discussions and
numerous registered users, the informational influence on all virtual
community`s constituents at once is impossible.
2. RELATED WORKS
The rules, following which a state could combat informational influence of
virtual communities, are presented in [1, 2]. They are:
• Applying force - shutting down servers;
• Legal – prosecuting virtual community members;
• Monitoring and exercising of informational influence methods with
the aim to fight the informational influence of virtual communities.
Monitoring and exercise of informational influence methods to fight virtual
informational influence of communities is proved to be in the long run the
most efficient of three enlisted previously methods. These methods give
opportunity not only to cease or slow down virtual communities activities
but change their ideology.
In the research [3] the model of virtual community informational space,
which consist of exterior and internal informational space, was created.
Taking into account the model of informational space presented in [4, 5]
was worked out informational hazard index. It is utilized to measure the
informational hazard level. The following constituents of informational
space are considered:
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• The number of virtual community members;
• The amount of operating assets;
• The amount of virtual community content;
• Discussion relations structure of a virtual community.
In order to resist and fight informational hazards in virtual communities it
was researched how to choose the appropriate strategy of informational
influence on internal virtual community space.
The strategies of influence on the internal space of the virtual community
were worked out according to the rules of counteraction to informational
hazards in virtual communities.
Strategy 1. Discussions banning, that means decrease in discussions and
members number.
Strategy 2. Destroying discussions` relations, doesn`t involve without
diminishing discussions and members number.
Strategy 3. Destroying discussions` relations, with the aim of forming
groups of discussions, doesn`t involve without diminishing discussions and
members number.
Conducted researches [6] showed that the most efficient in influencing the
structure of virtual community`s informational space are mixed strategies.
Before making this deduction the following influence types were studied:
• Discussions’ relations destroying by means of discussions banning;
• Informational influence on discussion content in order to reduce the
degree of messages relevance to the discussion`s topic, which would
result in transferring the discussion to rival virtual community.
3. STATING THE PROBLEM
In this paper the following model of internal informational space [3] is
employed:
)itytualCommunShadow(Vir)itytualCommunMember(Vir
al(Tread),LinkIntern),itytualCommunThread(VirmunityVirtualComInfSpace
ii
ii
,
)( =
where )itytualCommunThread(Vir i means the totality of the і-th virtual
community discussions;
where )itytualCommunThread(Vir i means the totality of the і-th virtual
community discussions;
)(ThreadalLinkIntern means discussions relations matrix of the і-th virtual
community;
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)itytualCommunMember(Vir i means the set of registered in social networks
і-th virtual community participants (members);
iN
j
ji ThreadMember)itytualCommunMember(Vir
1
)(
=
=
,
where
)( jThreadMember
represents the set of registered in social networks
j-th discussion participants;
iN represents the number of і-th virtual community discussions;
)itytualCommunShadow(Vir i represents the set of registered in social
networks users interested in the discussed in the i-th virtual topics;
iN
j
ji )eadShadow(Thr)itytualCommunShadow(Vir
1=
=
,
where
)eadShadow(Thr j
stands for the set of registered in social networks
users, who despite being interested in a discussion do not participate in it;
iN stands for the number of і-th virtual community discussions.
Provided:
)itytualCommunShadow(Vir)itytualCommunMember(Vir ii ≠ .
A virtual community is presented by means of matrix method [7, 8] as a
disconnected, undirected graph.
),( AVG =
where V denotes the set of vertices that represents the totality of the i-th
virtual community discussions )itytualCommunThread(Vir i ;
A denotes the graph`s G adjacency matrix that represents the elements of
virtual community discussions relations matrix;
)(ThreadalLinkInternA =
According to [3] the matrix of relations between the discussions of the i-th
virtual community has the following look:
,)(
*nnijlinkThreadalLinkIntern =
where ijlink
indicates the existence of hyperlinks between the i-th and the j-
th discussions of the virtual community;
n denotes the number of discussions in the virtual community;
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The presence of a hyperlink between the i-th and the j-th discussions in the
virtual community is determined in the following way:
Or:
where iersThreadMemb denotes the set of the i-th discussions members.
Vertices weights could be calculated on the grounds of discussions`
characteristics )( iThreadSim and the following discussion model [3]:
)(),(,,, iiiiii ThreadLinkThreadPostersThreadMembriptionThreadDesceThreadTitlThread =
where ieThreadTitl represents the i-th discussion title;
iriptionThreadDesc represents the i-th discussion description;
iersThreadMemb represents the set of the the i-th discussion members;
{ } )(
1
)(
iPT
N
jiji PostThreadPost =
=
represents the set of the messages, that
constitute the i-th discussion;
)( iPT
N represents the number of messages in the the i-th discussion;
)( iThreadLink represents the set of hyperlinks, that are in the i-th
discussion informational content.
Thus vertices weights are denoted as
niii ersThreadMembcardThreadSimV ,1
)(),( =
=
where )( iThreadSim stands for the degree of relevance of the i-th
discussion posts to its topic;
)( iersThreadMembcard stands for the number of discussion members.
Thus, the aim is, by means of the graph theory algorithm, to solve the
problem of finding the shortest list of the virtual community discussions,
which deletion would reduce the information hazard index of the virtual
community to the threshold level.
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4.1 Block 1
Discussion groups have to be formed according to the following rules [4,5]:
• The group can`t be empty, it should consist at least of one
discussion.
• A virtual community can contain from 1 to n groups (n means a
number of discussions in a virtual community), therefore the group
can contain from 1 to n discussions.
• All discussions are interconnected with internal and exterior
hyperlinks or have common members. Discussions, not connected
with any discussion of the group, found another group.
• All discussions of the group have no internal or external hyperlinks
and no common members with the discussion from the other groups.
Otherwise, the groups have to be referred as to one.
Next step is to assess the value of the formed groups. The formula for
calculating virtual community group value is presented further:
( )
( )
( )∑
∑
∑
=
=
=
⋅−
−
⋅⋅
⋅⋅=
)(
)(
)(
1
1
1
)()(
)()(ln
)()()(
iGroup
iGroup
iGroup
M
j
jj
M
j
jj
M
j
jji
ersThreadMembcardThreadSim
ersThreadMembcardThreadSim
ersThreadMembcardThreadSimGroupValue
where jersThreadMemb
represents the set of the j-th discussion participants;
)( jThreadSim
stands for the degree of the j-th discussion`s topic relevance;
)( iGroup
M stands for the number of discussions in the j-th group.
The degree of relevance is calculated by the equations described below [3]:
( )( )
( )( )∑
∑
=
=
+
−
= )(
)(
1
)()(
1
)( iThread
i
iThread
N
j
i
flood
j
Thread
N
j
ij
i
ThreadPostcardN
ThreadPostcard
ThreadSim
where
)( ij ThreadPost+
the set of the і-th discussion’s positive messages;
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)()(
i
flood
j ThreadPost
means the set of the i-th discussions messages that in
light of the virtual community subject matter convey no useful information;
)( iThread
N means the number of the і-th discussions messages.
And
( )
( )∑
∑
=
=
+
= )(
)(
1
1
)(
)(
)( iThread
iThread
N
j
ij
N
j
ij
i
ThreadPostWeight
ThreadPostWeight
ThreadSim
where
( ))( ij ThreadPostWeight +
denotes the weight of the і-th discussion`s
positive messages;
)( iThread
N denotes the number of the і-th discussions messages.
( )
)(
*
)(
*
)(
)(
i
ijiThreadCentroid
i
ThreadCentroid
Postw
ThreadCentroid
ij
M
w
ThreadPostWeight
∑
∈
=
,
wherе
*
)( iThreadCentroidw
represents the weight of the keyword from the і-th
discussion centroid, which is in the j-th post of the i-th discussion;
)( iThreadCentroidM
represents the number of the keywords from the і-th
discussion centroid, which are in the j-th post of the i-th discussion;
The group that has the highest value of all other groups and contains more
than two elements is to be selected.
4.2 Block 2
Before applying informational influence, it is necessary to decide on a
discussion or several suitable for informational influence discussions.
Further step is excluding the discussion from the virtual community, this
can be achieved either by applying power (shutting down a discussion) or
by informational influence (reducing the degree of the discussion topic
relevance and discussion transfer to the rival virtual community).
4.3 Block 3
Calculating the information hazard index for the virtual community that has
undergone enlisted above changes [4,5]:
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5. DISCUSSION GROUPS FORMING
Due to the fact that the virtual community is presented by means of the
matrix method, the algorithm of the graph partition into as dense as possible
graphs is used.
To perform this, the adjacency matrix A is exploited. All the diagonal
elements of the adjacency matrix A are equal 1, as long as, each vertex is
reachable for itself.
Following the parallel algorithm of constructing reachability matrix on the
basis of the graph [9], build the reachability matrix R.
The constructing reachability matrix algorithm consists of the following
steps:
1. Create a reachability matrix .
2. Using the general formula, create a reachability matrix for the k
subsequent iterations.
3. Repeat the step 2 until the condition is satisfied:
The matrix where the entry of 1 in row i, column j indicates a path from i to
j with just one edge
1=ijr
, is the result of parallel algorithm of constructing
reachability matrix.
Having grouped the matrix R by shifting the columns and rows that have
similar ordinal numbers, you will build a block diagonal matrix , where
the each group of elements denotes a group of virtual community
discussions.
If all matrix elements equals 1, a virtual community is represented only by
one group.
If from all elements representing a vertex, only a diagonal element equals 1,
the discussion is isolated.
6. DETERMINING THE SUITABLE DISCUSSION
Matrix product of n copies of adjacency matrix properties [7, 8] are
employed to choose a discussion. Only the existence of the trace between
the vertices is of interest, therefore in the matrix exponentiation algorithm
arithmetic operations are substituted with logical operations (Addition with
disjunction and Multiplication with conjunction).
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Besides a discussion list, the prospective structure of the internal and
external information space of the virtual community after informational
influence is sketched.
For the further virtual community monitoring is determined the observation
window. It gives opportunity to see the results of the informational
influence.
During the revised social network monitoring are taken all measures to form
the virtual community with the determined subject matter.
The list of prohibited discussions is made before the revised monitoring.
9. EXPERIMENTAL PART
The calculations were made for the virtual community model with the
following features showed in Table 1.
Table 1. Characteristic features of the virtual community’s models graph
№ Graph metrics Meaning
1. Vertices (discussions) 500
2. Edges 737
3. Connected components 1
4. Maximal number of the vertices in the connected
component
500
5. Maximal diameter of the graph 500
6. Average diameter of the graph 12
7. Graph`s density 5,72
Presented characteristic features of graph of the virtual community model
correspond to the previous investigations of social networks structure [10,
11].
Additional features of the community`s discussions are presented in Table 2.
Table 2. Characteristics of the virtual community`s discussions
№ Discussions` characteristics Meaning
1. Minimal number of members 100
2. Maximal number of members 1000
3. The lowest degree of posts relevance to the topic of the
discussion
0,5
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10. CONCLUSIONS
The set in the beginning of the research goals were reached. In other words
the problem was formulated and applying graph-theoretic methods was
developed an algorithm of making the minimal list of virtual community
discussions suitable for the informational influence aiming at informational
hazard reduction to its threshold. By repeated algorithm application, the
feedback of informational influence on the internal space structure of a
virtual community is taken into account. Moreover the list of unsuitable for
informational influence discussions (prohibited discussions) is formed. The
list contains strongly moderated discussions (administrators and moderators
constantly delete undesirable content) and discussions, informational
influence on which caused negative results on the participants of the
discussion. Experiments results proved that the highest informational hazard
index reduction ensued from destroying the structure of internal
informational space. Causing a decrease in virtual community discussions
count (members of virtual community count) appeared to be less efficient.
The maximal informational hazard reduction occur, either by forming
separate groups of discussions according to the Strategy 3 or by forming
large quantity of isolated discussions corresponding to Strategy 2.
11. REFERENCES
[1] Huminskyi, R.V., 2012. Virtual communities as a subject of informational security of
the state. Scientific and Practical Journal of Informational Security, 3(56), pp. 18-25.
[2] Peleshchyshyn, A.M., 2013. Threats to informational security of a state. Scientific and
Technical Journal of Ukraine Air Force, 2(11), pp. 192 - 199.
[3] Peleshchyshyn, A.M. and Huminskyi, R.V., 2014. The model of informational space of
the virtual community. Eastern-European Journal of Enterprise Technologies, 2/2(68),
pp. 10-16.
[4] Peleshchyshyn, A.M. and Huminskyi, R.V. Evaluation of informational hazards in the
process of virtual communities functioning. In: National Aviation University, 4th
International academic conference ITSEC. Kyiiv, Ukraine. 21-24 May 2014. Kyiiv:
National Aviation University, pp. 59 – 60.
[5] Huminskyi, R.V. and Peleshchyshyn, A.M., 2014. An assessment of informational
threat in the functioning process of virtual community. [online] Cybernetic Letters.
Available at: <http://www.cybletter.com> [Accessed 05 August 2014].
[6] Peleshchyshyn, A.M. and Huminskyi, R.V., 2014. The selection of the strategy of the
informational influence on informational space of the virtual community. In: Lviv
Polytechnic National University, 3rd International Academic Conference on
Information, Communication, Society. Lviv, Ukraine. 19-21 May 2014. Lviv: Lviv
Polytechnic Publishing House, pp.30 – 31.
[7] Berge, C., 1958. The theory of graphs and its application. Translated by A.A. Zykova.,
1962. Moscow: Foreign Literature Publishing House.
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[8] Zykov, A.A, 1987. The fundamentals of the graph theory. Moscow: Chief editorial
office of physics and mathematics literature.
[9] Kniazkova, A.V. and Volchenskaia, T.V., 2014. The parallel algorithm of finding
reachability in a graph. [online] Fundamental Researches. Available at: <http://
www.rae.ru/fs/?section=content&op=show_article&article_id=10003049> [Accessed
05 June 2014].
[10]Abramov, K.G., Monachov, Ju.B. and Bodrov, I.Ju., 2011. To the question of social
networks topology modeling. In: SFedU (Southern Federal University), 5th All-
Russian scientific-practical conference on theory and practice of imitational modeling.
Saint Petersburg, Russia. 19-21 Oktober 2011. Saint Petersburg: Southern Federal
University, pp. 11 – 14.
[11]Hubanov, D.A. and Chkhartishvili, A.H., 2014. Formal and informal connections of
users of Facebook social network. In: IMP RAS (The Institute of Management
Problems of the Russian Academy of Sciences), 12th All-Russian conference on
management issues. Moscow, Russia.16-19 June 2011. Moscow: The Institute of
Management Problems, pp. 301 – 309.
This paper may be cited as:
Huminskyi R.V., Peleshchyshyn A.M. and Holub Z., 2015. Suggestions for
Informational Influence on a Virtual Community. International Journal of
Computer Science and Business Informatics, Vol. 15, No. 1, pp. 47-65.
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traditional telephoning system for both VoIP service provides in terms of
infrastructure cost and user calling cost. A 2010 study by IBISWorld
showed that VoIP services have the best growth within the Information
Technology industry from 2000 to 2009 with a growth of 179,036% [1].
VoIP is a technology that provides circuit switch like telephone service over
an IP based network [2], its involves transmitting voice or media data over
the internet by converting analogue signal into digital signals by the means
of codec and uses Real-time Transport Protocols as the transport media [3].
Because of the increase in acceptance of VoIP technology, there is a need to
secure VoIP traffic as the media networking protocol used in transmitting
VoIP packet Real-time Transport Protocols has no security feature [4].
However, the increase in both packet size and processing
(Encryption/Decryption) time of each of the encryption algorithms due to
the encryption key size, cipher block size of the encryption algorithms
creates an added overhead on VoIP packets during VoIP transmission; this
will have a clear effect on the QoS in terms of e2e delay and the rate at
which packet are dropped depending on the Queue buffer and the jitter
buffer algorithms. In today’s world where VoIP application users such as
Skype, Apple Face Time are growing rapidly especially in the mobile
platform sector and these users are competing with each other and other
network devices for bandwidth, the need for selecting the best encryption
algorithms and best mode of operation (stream/block cipher mode) with the
highest threshold in terms of users in order to mitigate the cost of encryption
on VoIP transmission and to effectively utilize the available network
bandwidth cannot be over stated.
This work is aimed at determining the threshold at which Quality of Service
(QoS) will be affected when AES, DES, 3DES encryption algorithms are
discretely implemented on the VoIP Crypto-Engine in stream or block
cipher mode. This will be achieved by quantifying the overhead produced
by stream and block ciphers in terms of latency (e2edelay) and rate of
packet loss during a pre-established VoIP transmission. On the specifics,
target objectives tend towards; achieving a clear review of related works
that shed light on the cryptographic overheads accrued on real time
applications such as VoIP. To achieve through critical analysis, the design
of well-defined Test parameters for performing the simulated experiment
covering parameters such codec, cipher, bandwidth, network topology.
Determine through experimental simulation, the encryption (AES, DES, and
3DES) algorithms and the mode of encryption (stream/block mode) with the
highest threshold point at which the QoS is affected in a VoIP call system.
And finally to a resource pool for network and security computer society in](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-69-320.jpg)
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both academia and industry, for the adequate selection of the best
encryption algorithms, the best mode of operation (stream/block), combined
with the best voice codec’s for implementing in secure VoIP transmission.
Because of the lack of security mechanism in Real-time Transport Protocol
(RTP), Secure Real-time Transport Protocol (SRTP) was developed in
2004. SRTP employs the use of cryptographic algorithm and hash functions
to provide confidentiality, integrity, authentication and anti-reply of data
transmitted over RTP [5]. This discourse will focus strictly on the
cryptographic algorithms used by SRTP. By default SRTP supports
symmetric encryption algorithm for media transmission of the VoIP packet.
VoIP packets are segmented into four sections the IP header, UDP header 8,
RTP header and Payload. Packet size may be different depending on the
voice codec used which determine the payload size; overall the packet
header size is 40 bytes (IP header 20bytes, UDP header 8 bytes, and RTP
header 12 bytes). Since SRTP encrypts the payload not header information
our focus will be on the payload size.
Although VoIP uses two main protocols; the signalling protocol and media
transfer protocol, this work focuses on measuring the effect of encryption
algorithms on media transfer protocols (RTP) only for pre-established VoIP
transmission. Latency (e2eDelay), Packet Jitter and Packet Loss Ratio are
the key network metrics used to determine the QoS of VoIP transmission.
Precisely, only the effect of latency (e2eDelay) and the packet loss rate of
the encryption algorithms will be determined. Encryption Algorithms to be
covered include; Advance Encryption Standard (AES) with 128 bits key,
Data Encryption Standard (DES) with 56 bits key and Triple Data
Encryption Standard (3DES) with 56 bits key. The effects on latency and
packet loss rate of the above listed encryption algorithms will be determined
on G.711 and G.729 voice codec support VoIP network.
2. VOIP SECURITY: RELATED WORKS
Voice over Internet Protocols (VoIP) is a technology that transmits real time
data such as voice and (or) video over the internet [6]. In other words, VoIP
provides a Public Switch Telephone Network (PSTN) or Circuit Switch
Telephone Service over a Packet Switch system such as the Internet or
Intranet [7]. In the traditional PSTN network, analog voice signals are
transmitted over the network, this is not the case in VoIP. VoIP converts
voice signals by the use of codec algorithms; codec’s converting the
analog voice signals into digital packet, thus enabling voice signals to be
transmitted over an IP-based network [8]. Unlike PSTN that supports a](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-70-320.jpg)
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dedicated end-to-end connection between the two end users, VoIP packet
transmission does not require a directed channel, but rather employs UDP,
which is a connectionless transport protocol. In VoIP, how the packets get
from source to destination is not as important as the speed taken by packets
to reach destination from the source [9]. VoIP supports the use of IP-phones
(phones connected to the router), computer-to-computer communication,
soft-phones (software based phones such Skype) and also in combination
with PSTN or SIP-Based VoIP (internet/intranet), figure 1 shows a basic
architecture of a VoIP system [10].
Figure 1: VoIP Architecture 1(VoIP 2005)
Basically, two categories of protocols come functional in the operations of a
VoIP system; signalling protocols and media transfer protocols. While
signalling protocols help to ensure end-to-end connection and (or)
disconnection between two end users [11] , the media transfer protocols aid
the actualization of real-time voice and (or) video packet transmission [12] .
2.1 Security Mechanisms for VoIP
It follows that by initial (default) design, both the signalling and media
transfer protocols like SIP and RTP respectively have no security features
attached, thus needing supporting protocols like SPD and RTCP
respectively. This feature makes VoIP an easy target for attackers to
eavesdrop on VoIP conversations and modify both the signalling and media
transfer protocols [13] . In order to overcome these flaws, the three
principles of security (Confidentiality, Integrity and Authentication) are
implemented on both protocols.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-71-320.jpg)
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2.1.1 Confidentiality
This defines a concept protecting data or information from unauthorised
accessed. It is achieved by encrypting the media transport protocols using
symmetric encryption algorithms running in stream or block cipher modes
to encrypt/decrypt VoIP packet or blocks of VoIP packets. SRTP was
developed to provide RTP with a means of ensuring confidentiality. SRTP
encrypts only the payload section of the VoIP packet, leaving the Header
information (IP/UDP/RTP) section unencrypted [14]. All VoIP packets
traffic are encrypted at source and decrypted at the destination by a Crypto-
Engine.
By way of elaboration, stream ciphers are a family of encryption algorithms
where each bits on a plaintext such that M = m1+ m2+m3 are encrypted
using a pseudorandom bits generated encryption key called a key stream
such that K = k1 + K2 + k3 using a XOR Red operation such that EK(m) =
Ek1 m1 k1=C1 to create a cipher C1 [15]. However, block ciphers are
encryption algorithms that encrypt blocks of data at a time [16]; instead of
one bit at a time like stream ciphers. Block ciphers segment the bits of
plaintext into blocks usually a fixed size of 128 bits in the case of AES [17],
but may differ with other ciphers. Using mode operation a random bits
generated key is combined with bits from the previous successive ciphers to
encrypt each block of data [18]. When used in VoIP, packets in blocks
of128 bits of size for AES are encrypted and decrypted by the crypto-engine
using a random key from each successive block of bits [19] , [20] .
2.1.2 Integrity
This principle saves from unauthorised modification of data or information.
The integrity of VoIP traffic is archived by the use of a Hash function
algorithm. By default HMAC-SHA1 is used to ensure that VoIP packets
have not been altered during transmission. Integrity is also implemented in
VoIP when establishing a session in SIP. Typically, hashing the VoIP
packet includes both the VoIP payload and the information Header. At the
source end a hash value of RPT or SRTP VoIP packets is generated and the
integrity is checked at the destination end by generating its own hash value
and comparing it against the hash value of the received.
2.1.3 Authentication
The security by Authentication feature used in VoIP is performed on the
Session Protocols, in order to authenticate end-to-end establishment of VoIP
session, asymmetric encryption algorithms are used. The two end users](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-72-320.jpg)
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negotiate a cipher suite to use in order to create a master key [14]. For
instance, the SIP protocol doesn’t support any security mechanisms, but by
the use of well-known, publically tested internet security mechanisms such
as HTTP digests; it provides a mechanism for authenticating VoIP users.
The authentication process can be hop-to-hop or end-to-end [21].
2.2 VoIP Operation: Wired and Wireless Modes
In a wired network scenario, VoIP system operates such that the user
obtains an IP address from a DHCP server. The VoIP terminal (softphone)
registers with a call server (PBX); where voice services access is granted
after a completed registration process. For a call to be placed or received
with the terminal device, the call server adds the registered device to a
Domain Name System (DNS) server, thus enabling a directory lookup on an
IP network. When Paul dials Alice, The destination number (Alice’s) is
routed to a call server which in turns notifies the destination terminal
(Alice). Once the destination terminal (Alice) accepts the call, a notification
is sent back to the call server and the call server sends a notification to both
terminals that a channel is available to start a conversation.
However, the service flexibility in terms of mobility has seen wireless VoIP
(VoIPoW) advancing farther than landline networks. VoIPoW enables
mobile devices such as laptops, mobile phones, two way radios etc., to place
and receive VoIP calls on a wireless network infrastructure either through
Wireless LAN or Wireless WAN. Just like in VoIP wired landline network,
in VoIPoW; the user terminal connects and registers with a call server by
obtaining an IP address from a DHCP server, while SIP and RTP protocols
supported by TCP/UDP helps the user to initiate and engage in a VoIP
conversation by routing the compressed voice packet over a gateway to the
destination user. Thus, VoIP employs the use of multiple protocols that
support IP-based network, wired or wireless radio communication
technology and other legacy communication systems such as PSTN and
ISDN. It can also be deployed on a multitude of different architectures.
For instance, Session Initiation Protocol (SIP) is a signalling protocol that is
an application layer protocol on the TCP/IP network model which is based
on request-response. It implies a client/server based architecture usually
connecting two end users via a proxy server. The protocol is used to
establish, terminate and modify sessions in VoIP over an IP based network
[22]. SIP is also supported by Session Description Protocol (SDP); a
protocol that carries the session descriptions such as session information
and media information [23]. SDP is transmitted with the SIP packet during
the first ‘INVITE’ packet and contains the session information that consists](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-73-320.jpg)
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of the session name and proposes the number of times the session is active,
and the contact detail of the source of the session. The media information
consists of type of media (voice/video) and the transport protocol
information (RTP/UDP/IP).
Real-time Transport Protocol (RTP) is another protocol-instance classified
as a Media Transport Protocol. It comes useful when transferring real-time
data such as voice or any media over the internet [24] either over a multicast
or unicast network, and it is also supported by control protocol called Real-
time Transport Control Protocol (RTCP). RTCP carries the description of
the data packet being transmitted by RTP and is also used to determine the
Quality of Service [25]. It contains information about the RTP packet such
as; information about the users, and information that is used to measure
Quality of Service parameters like number of packet loss and jitters. Both
RTP and RTCP are designed to be completely independent from transport
protocol (TCP/UDP) on the TCP/IP layer model [26].
2.3 VoIP Security and QoS: Approaches and Shortcomings
With relativity to VoIP Networks, quality of service (QoS) can be defined
as the quality of voice/video during a VoIP transmission [27], and it is
measured based on acceptable criteria’s set by international standard
organizations like the International Telecommunication Union (ITU) and
the Internet Engineering Task Force (IETF). In broader terms, network
criteria for measuring service efficiency include; latency, packet loss and
jitter. These too are applicable to VoIP. However, the economic constraint
of an encryption algorithm on QoS depends on the encryption cipher and
codec used [28]. In other words, the length of the encryption key and the
mode of encryption (stream/block ciphers) combined with the processing
time for encoding and decoding of the VoIP payload by the codec
determines the budget on the QoS. Thus a logical solution to achieving our
goal is to study the effect of voice codec when combined with the
encryption algorithms and how they affect latency, packet loss and jitter
during VoIP transmission.
2.3.1 Latency
Latency or e2edelay in VoIP is the total round-trip delay time for a bi-
directional VoIP packet transmission between two end users [29]. It can be
measured in two ways; 250ms for a round-trip from source to destination
and back to the source, or 150ms for one-way trip from source to
destination, which also includes the delay time for the packet to travel along
multiple hops over the internet as specified by the ITU-G 11.4 standards. It
is calculated by defining three parameters in VoIP transmission; Dtransmitter,](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-74-320.jpg)
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Dnetwork, Dreceiver; where Delay is obtained by summing the three parameters
[30]. The size of the encryption key and the mode of operation
(stream/block) by the cipher algorithm will lengthen the encoding and
decoding processes of the codec which will in turn increase the latency
delay of the VoIP packet [19]. A study on the effect of DES/3DES/AES-
128-256, RC2 and Blowfish encryption algorithm on latency during a VoIP
transmission using different bandwidths (34Kb, 64Kb) shows thus; when
using 34kb bandwidth each of the encryption algorithms generate latency
when compared with the use of firewall and without the use of firewall.
Blowfish generates the highest latency with a time of 0.00001600 seconds.
While a 64kb bandwidth, with or without a firewall generates almost the
same latency with 3DES yielding the highest latency when compared with
the other algorithms [31].
2.3.2. Jitter
Jitter defines the measured variation in each successive packet arrival time
due to transmission delay [32]. This occurs when each successive packet
have a different latency, since packets are transmitted over the network by
the UPD transport protocol each packet will take a different pathway, and
the arrival time will differ from source to destination A jitter buffer
algorithm is used to assemble the packet but at the cost of time. If the packet
cannot be reassembling within 150ms the packet is dropped. The
acceptable level of jitter is about 20ms regardless of the number of multiple
hops between the source and destination, if the time increases above 20ms
the buffer cannot reassemble the packets in correct order making the
conversation sound choppy [30].
The study of the impact of security mechanism on VoIP by measuring the
effects on the encryption algorithms (3DES/AES-128-256/Blowfish and
RC2 on 38k, 64k, 100M network bandwidths) on selected criteria as
presented by (Talevski 2011) shows a high ratio of jitter on VoIP when
there is no encryption and using a firewall while at 100M the jitter ratio is
0%. However, when using 38kb RC2 records the lowest ratio in comparison
with 3DES, Blowfish, AES 128, AES 256 and DES. But when using 64k
bandwidth RC2, AES 128, AES 256 and DES all yield lower ratios as
compared with 3DES and Blowfish. Interestingly, when the bandwidth is
100Mbps there is no effect on the jitter on any of the encryption algorithms
[33].](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-75-320.jpg)
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2.3.3. Packet loss
This defines the ratio of packets dropped due to limited jitter buffer size at
the destination end, or packets that did not reach their destination [34]. An
acceptable percentage of packet loss should be below 5%, which includes
multiple hops between source and destination of the VoIP transmission.
When the packet loss is greater than 5% the destination end user will only
hear air space. The study by [33] shows that using 38Kbps of bandwidth in
all the encryption algorithms (3DES/AES-128-256/Blowfish and RC2),
packet loss ratio is above the acceptable limit of 5% except for 3DES
which yields 4% in 64Kbps of bandwidth. However, for 100Mbps speed,
the packet of the algorithms is below or within the acceptable limit, with or
without a firewall component attached.
Therefore, it follows that the budget of encryption algorithm on QoS
generally depends on the type of algorithm used, the length of the
encryption key and the network bandwidth. The study presented above
shows that only latency and packet loss bear negative impacts on the QoS.
Its however amazing to note that the result of the two experiment show that
encryption algorithms has a positive effect on the jitter of VoIP packets
when compared to plain VoIP packet transmission; this might not be
unconnected to network topology setup, since in all the test adopted a single
point-to-point connection between the two computers there is no flexibility
for VoIP packet taking multiple paths form source to destination
The proliferation of varying VoIP applications with varying platform
dependence necessitates a study for the determination of the economic
constraints for the implementation of encryption on network performances
and CPU cycle performances and the affect it will have on quality of voice
or video between two end users.
A comparative study of the effects of AES in both stream and block cipher
modes on the QoS results relative to end-to-end delay between two end user
[35]. The objectives of the study included; determining the errors generated
by the two cipher modes when packets are decrypted at the destination end,
and the effect of the errors on the QoS. Secondly, determining the effect of
the two cipher modes on packet size, crypto-engine and packet loss on the
QoS in terms of end-to-end delay. The authors used a GSM 06.10 Codec
and AES algorithm for both stream and block mode to encrypt and decrypt
RTP on the crypto-engine. The result showed that the packet size, crypto-
engine and the packet loss all bear effects on the end-to-end delay between
two end users. This outcome was further consolidated by [36], in his work.
He worked on the effect of AES on packet size and the throughput of the
crypto-engine when AES is operating on stream and block cipher mode.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-76-320.jpg)
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Considering packet size scenario, his work showed that that each of the
cipher mode has an effect on the packet size but AES operating on block
cipher mode has a greater effect on packet size when compared to stream
cipher mode, [36]. Considering crypto-engine, AES was used on the two
cipher mode and the crypto-engine saturated by increasing the PPS by 25
PPS in every 30 seconds for each four (4) VoIP packet transmitted with the
size of 60, 100, 250, and 100 for each of the four packets respectively.
While focusing on packet size, the study proves that each of the cipher
mode has an effect on the packet size but AES operating on block cipher
mode has a greater effect on packet size when compared to stream cipher
mode, the outcomes are shown in figures 2 and 3 [36].
The maximum threshold of the two cipher modes before the QoS is affected
is indicated by a negative slope. In terms of packet loss, Mean Opinion
Score (MOS) was used to evaluate the effect of packet loss on QoS of the
two cipher modes on end-to-end delay. As would be noted, AES as stream
cipher mode has less packet loss in end-to-end delay compared to block
cipher mode, because of the use of key stream by stream ciphers.
Summative, it implied that AES on stream cipher mode has a better
performance than when run on block cipher mode that is before loss due to
synchronization error [36].
Figure 2: Effects of Stream and Block Ciphers on packet size and
throughput [36]](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-77-320.jpg)
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Figure 3: Packet Loss [36]
In another related experiment by [37], the focus was on a family of block
ciphers that uses linear prediction as mode of operation. The authors
determined the threshold point at which the QoS will be affected based on
VoIP traffic in terms of call volume. Using iterative block cipher to encrypt
the VoIP packet in a simulated network environment the authors used IPsec
for end-to-end transmission of VoIP packets with a total number of 600
users on the network. The users are interconnected using switches, routers
and a state full firewall and G.729 codec with DES/3DES/AES encryption
algorithms used in block cipher mode. VoIP packet with G.729 codec
having a payload size of 10, 20, 30 and 40 bytes for encrypted VoIP packets
using DES/3DES and 10 byte, 20 byte and 30 byte for plain VoIP packets
were transmitted. The outcome showed that in plain VoIP traffic the packet
loss started at about 160 calls when the payload is 10 bytes in size and the
end-to-end delay is within the acceptable limit. QoS was unaffected
probably due to compression or the reduction of the throughput by the
codec and combined with the buffer and the FIFO algorithm used by the
authors [37].
The end-to-end delay when encryption was applied was above 200ms which
is beyond the acceptable limit. However, packet loss consideration revealed
a three-time increase in the payload size; especially when the payload size is
10 bytes and also observed that the rate of packet loss is lower with
increased payload size when using DES/3DES encryption algorithm. For](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-78-320.jpg)
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ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 77
call volume traffic the study revealed that for all payload size when G.729
codec is used with DES/3DES; the rate of packet loss will be above the
acceptable loss limit [38].
The works reviewed took differing approaches for answering the question
‘which algorithm is better in terms of the effect on the QoS of the VoIP
network?’ The outcomes are quite similar with respect to latency, packet
loss with each laying emphasis on direct relation between latency, packet
loss, and jitter to the type of encryption algorithm in the crypto-engine, the
cipher mode of operation, length of the encryption key and the payload size
(codec). However, they both bear varied strengths and limitations that
basically tended towards methodology, topology and parameters. While the
former used a point-to-point network connection between the two hosts;
which restricted the results to only VoIP in a peer-to-peer network, and
focused on the use of only AES encryption algorithms, without
considerations to other encryption algorithms like DES, 3DES, Blowfish,
etc. The latter simulated a real world application of VoIP network with
routers, switches, and firewall but whose result is only restricted to
encryption algorithms running on block cipher modes only.
3. MODEL SIMULATION
This covers a detailed overview of the experiment test-bed and the
simulation parameters that will be used to evaluate the effects of encryption
algorithms on QoS; when implemented in Stream and Block ciphers mode
to secure VoIP communication. The methodology for performing the
experiment and the simulation parameters will all be implemented in NS2
network simulation environment. Such parameters as the VoIP codec, the
type of encryption algorithms, the length of the encryption key, the mode of
encryption (Stream or Block cipher mode), the network topology and the
type of transport protocols (UPD/TCP), the media transfer protocol (RTP)
and the network bandwidth will be considered. The comprehensive
simulation parameters setup is captured in table 1.
3.1 Simulation Parameters
As noted earlier, the key components that constitute the basis for secure
SIP-Based VoIP transmission include; voice codec, encryption algorithms,
and networking properties such as bandwidth, propagation delay of the
network links, queue type and size [39]. Thus, these will be used for the
simulation. Table 1 shows the details of the simulation setup as would be
used.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-79-320.jpg)
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when calculating and comparing the overhead of each of the three
encryption algorithms, it demonstrates that AES and DES (in stream cipher
mode on G.711 (64Kbps) and G.729 (8Kbps). VoIP support codec are faster
and have a higher threshold in terms of number of calls before the e2e delay
and the rate of packet loss exceeds the acceptable limit for encrypted and
plain VoIP e2e delay and packet loss rate. The simulation also implies that
there no significant difference in both e2e delay and packet loss rate for
3DES in stream and block ciphers modes on G.711 (Kbps) and G.729
(8Kbps) VoIP supported codec, this is because 3DES has a drastic effect
both the e2e delay and packet loss rate at similar number of calls. Although
the study only focuses at measuring the effects of stream and block ciphers
on VoIP in terms of e2e delay and the rate of packet loss during VoIP
transmission. It did not address the issues of the effect of Synchronization
and Bit Explanation errors generated by stream and block ciphers
respectively. Future work can tend towards measuring the cost of errors
generated by both cipher modes on pre-established VoIP transmission.
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This paper may be cited as:
Ani, U. P. D. and Mustapha, M. 2015. VoIP Security: Improving Quality of
Service through the Analysis of Secured Transmission. International
Journal of Computer Science and Business Informatics, Vol. 15, No. 1, pp.
66-90.](https://image.slidesharecdn.com/vol15no1-january2015-171208072428/85/Vol-15-No-1-January-2015-92-320.jpg)
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Vol 15 No 1 - January 2015
- 1. ISSN: 1694-2507 (Print) ISSN:1694-2108 (Online) International Journal of Computer Science and Business Informatics (IJCSBI.ORG) VOL 15, NO 1 JANUARY 2015
- 2. Table of ContentsVOL 15, NO 1 JANUARY 2015 Determination of the Account Personal Data Adequacy of Web Community Member .............................. 1 Solomia Fedushko, Yuriy Syerov, Andriy Peleschyshyn and Korzh Roman Layered Defense Approach: Towards Total Network Security............................................................13 Kalaivani Chellappan, Ahmed Shamil Mustafa, Mohammed Jabbar Mohammed and Aqeel Mezher Thajeel Millennials: Entitled Networking Business Leaders............................................................................23 Dr. Caroline Akhras Modeling of Citizen Claims Processing by Means of Queuing System ................................................36 Oleksandr Markovets and Andriy Peleschychyn Suggestions for Informational Influence on a Virtual Community ......................................................47 R. V. Huminskyi, A. M. Peleshchyshyn and Z. Holub VoIP Security: Improving Quality of Service through the Analysis of Secured Transmission ...............66 Uchenna P. Daniel Ani and Mohammed Mustapha IJCSBI.ORG
- 3. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 1 Determination of the Account Personal Data Adequacy of Web- Community Member Solomia Fedushko, Yuriy Syerov, Andriy Peleschyshyn and Korzh Roman Social Communications and Information Activities Department, L'viv Polytechnic National University, Ukraine, L'viv, S. Bandera Street 12 ABSTRACT This article considers the current problem of investigation and development of data verification of virtual community member by means of computer-linguistic analysis of web-members socio-demographic profiles for web-community member identification. The algorithm of formation system of lingvo-communicative indicators based the training selection of web-forum members is designed. This algorithm includes the formation of matrix of linguistic-communicative indicators and lingvo-communicative indicator weight coefficient determination. The computer-linguistic analysis of web-community members' information tracks is realized and verification of lingvo-communicative indicators of gender, age and sphere of activities of web-community member is established. Based on these results of the investigation the software algorithm of web-community members' socio-demographic profiles verification is designed and software "Verifier of the socio- demographic profile" is exploited. The account personal data adequacy of web-community member is determined by means of computation of the measure of the adequacy of personal account data. The calculation method of reliability of the result of the socio-demographic characteristics verification of web-community member is developed for constructing the socio-demographic profile of the web-member for web-community management. Keywords Socio-demographic profile, Software, Marker, Web-community member, Personal data, Validation. 1. INTRODUCTION The most important issues of web-communities content analysis today is analysis of web-users’ personal data [1, 2]. In spite of significant importance for the further development of this research field, methods of analysis are undeveloped in particular personal information on account of web- communities’ users. Development of web-community management software is a priority issue because the web-community is a popular and mass service at WWW, and existing software management tools are imperfect and not integrated. Authenticity of web-community user personal data is an important thing in the successful managing of web-communities.
- 4. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 2 The scientific task of validation method development for web-communities members’ personal data, including their socio-demographic characteristics, based on computer-linguistic analysis of the informational content is the current area of the research in computer linguistics. Since without linguistic methods and computer-aided tools this is the hardest task and requires significant time spending for web-communities administrators. 2. BACKGROUND STUDY The verification of personal data that is contained in the global system WWW is relevant and important research object in the following areas: Assessment of the online information reliability. The concept of content reliability, content relevance and reliability of highly specialized content. The formal review of perception of trust in the information among regular Internet. The personal data reliability and quality. Verification of socio-demographic users’ characteristics in WWW. The results of the research in the last scientific direction – of socio- demographic characteristics verification of users of the global environment WWW [3, 4] – are in demand of a wide range of experts in the organization and operation of web-communities, as such, that should ensure their performance and efficiency. This raises an important problem of the new methods and tools development that would have a proper scientific justification, formality, predictable performance and versatility for analyzing the socio-demographic characteristics reliability of the web- communities members. Socio-demographic characteristics Age Adult Teenager Natural sciences Formal science Gender Man Woman Education level Low educated Highly educated Sufficiently educated Sphere of activity Social sciences Figure 1. The structure studied by social-demographic characteristics of a web-user
- 5. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 3 For web-community user data validation, in order to improve web- communities management [5] and to improve target techniques in online advertising [6] is enough to analyze such basic socio-demographic characteristics (see. Figure 1). 2.1 The reasons of socio-demographic characteristics validation: Obtaining data from real users of social networking pages ("Facebook", "Twitter", "Habrahabr", "Google+", etc.), the popular online newspapers and magazines, dating sites ("LoveUA", "FindLove.in.UA", “12 Kisses”, “Dating foreigners website”) and web-forums (Ukrainian forum of programmers “Replace.Org.Ua”, “Domivka.Net: Ukrainian Forum”, “The first site of the Ukrainian community in Italy”) is urgent task for web- community administrators, police, private detectives (services that have been increasingly needed by users of global environment Internet) and individual user of any information resource. Verification and setting of web-users’ personal data who performs illegal actions that are offensive to opponents from psychological, financial, legal angle, in particular, who levies blackmail, sends hate mails, spreads false and aspersion information and conduct other electronic bullying. 2.1.1 Age Age category is chosen for specified age validation in web-community member due to a number of important factors: the presence of real online threats to Internet users with the age of 6 to 17 years (these include disclosure of personal confidential information, access to content that do not meet age peculiarities and adversely affect the physical and mental health of the child, online abuse, internet marketing crimes, etc.) and the need for screening age group of children who have applied or already are web- community member, that is intended only for adult web-space users. The characteristic features of a web-identity are self-expression and experimentation with the aim to make a definite impression on the users of the web-community and this is peculiar especially to growing age. The problem of age differentiation is that the penetration rate of children is increasing in web-communities, which are intended for adult users' communication, and this destroys communicative atmosphere of community and vice versa, children are increasingly claiming to be adult members. This situation can lead community administrator to criminal charges [7]. An example of web-communities for teenagers online communication is: "Student Forum|UNIVER-SITY", "chat for teens", chat "teenager", "chat for teens", "Just chat" and for adults "Our anecdote with Pepper" and others.
- 6. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 4 2.1.2 Education Many community administrators require web-community members to follow certain conventions of web-communication. Web-communication convention depends on the objective goal and projected scenarios of the web-community owners. An important factor in the possibility of participating in a web-community is a high literacy level of web-community member [8], level of higher education and skills. The method of screening illiteracy and with low education level web- community member will significantly reduce the time and financial costs, and managers' efforts to moderate web-community. In order to screen illiterate web- member it required to classify all members by the level of literacy, which will help to determine the likely level of each web- community member education. In the task automation research of detecting errors in the text are only considered character errors. Error analysis and data consolidation that were conducted by scientists, allows us to offer the errors typology and to classify members in the order of education level. 2.1.3 Scope of activity A web-member in a greater or lesser degree can belong to several areas of interest, as the impact of the content creation in web-communities serve a direction of education, professional activity and range of interests in spare time. However, the result of the analysis is to determine the scope of activity of web-community member. In the general scope of activities are classified as science fields in the following areas: Natural sciences; social sciences; formal science. This division is based on analysis of web-community members Internet communication with different scopes of activities. In web-community moderation that is intended for communication between members of certain areas, there many questions appear about level of professionalism, ethical principles, so filtering of web-users by scope of activities is a necessary and important task of community administration (government and policy portals) to improve the web-community position. 2.1.4 Gender In order to avoid gender conflicts in web-communities that are intended for women (L'viv Women's Forum “Cult of Beauty”, "Girls chat", Forum "L'viv-mama" et al.) and for men ("Man Forum", "Anti-feminine site" etc.) administrators of these communities need to enter a strict gender division. "Web-gender change", that is a web-user creation identity of the opposite sex, it is common on the Internet and is caused by the following factors as the impact of cultural gender stereotypes, expression of homosexual tendencies or transsexual or diffuse gender identity. So-called web-sex change is more peculiar to men due to several reasons desire to control and manipulate others, for women it is easier to get help and attract attention,
- 7. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 5 desire to power over other men, the study of the relationship between sexes and get new experience of Internet communication. 2.1.5 The geographic location Locating web-user with no verification data on computer IP-address of the web-community member using special software tools (CNGeoip, GeoLite Country, GeoLite City, IpGeoBase, GeoIp etc.) that can determine the belonging of IP-address to the level of countries and cities is the aim of geographic location identification of web-member. 3. LINGVO-COMMUNICATIVE INDICATORS FORMATION The formation system of lingvo-communicative indicators involves the content creation and processing of training selection of web-forum members. The algorithm of formation system of lingvo-communicative indicators based the training selection of web-forum members consist of these stages: I. Primary data collection II. Lingvo-communicative indicators formation III. Formation of the socio-demographic profile using the software "Verifier of socio-demographic characteristics " The research results are significantly affected by messages context and discussion topics. In view of this fact, the basis of this study is a diverse sample of user information tracks of all thematic chapters, more than 40 Ukrainian web-forums. Determination of Internet communication features - socio-demographic markers - is performed by analysis of information track of more than 640 members of Ukrainian web-communities. The study equally considered web-forum discussion that arises from a variety of interests and hobbies of young persons and adults, men and women with different levels of education. Computer-linguistic analysis of information track of Ukrainian web-forum members for grammatical, lexical-semantic and lexical-syntactic features are more specific to one particular socio-demographic characteristic value of certain web-community members. The experts set of gender and age linguistic features, professions and education features of web-users are formed based on: Researches of scientific theories and ideologies of domestic and foreign leading scientists, linguists, sociologists, psychologists, computer scientists;
- 8. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 6 Specialized dictionaries; Content analysis of the Ukrainian web-communities. The main aim of this process is to consolidate lingvo-communicative indicative features of Internet communication. Formation of lingvo- communicative indicator sets is in grouping indicative attributes in intuitive semantic groups. Visualization of the results is presented in tabular form in the classification of lingvo-communicative indicators for each value of all socio-demographic characteristics. 3.1 Formation of matrix of linguistic-communicative indicators Based on the lingvo-communicative indicators set experts form the matrix of lingvo-communicative indicators by computer-linguistic analysis of the web-community content for each value of each socio-demographic characteristics that is defined separately. As a result, for each value of certain socio-demographic characteristics we get a matrix of lingvo- communicative indicators: Vc,SDChVc,SDChVc,SDCh Vc,SDChVc,SDChVc,SDCh Vc,SDChVc,SDChVc,SDCh Vc,SDChVl_N,SDChInd_Ni,Vc,SDChInd_N1,Vc,SDChInd_N Vc,SDChVl_N,ji,j1,j Vc,SDChVl_N,1i,11,1 Vc,SDCh IndIndInd IndIndInd IndIndInd LKI where N_Vl - a feature that for each socio-demographic characteristics identifies a number of socio-demographic characteristic values; N_Ind - a feature that for each socio-demographic characteristics identifies a number of lingvo-communicative indicators of this socio-demographic characteristics value. Each matrix row is a vector of lingvo-communicative indicators of some socio-demographic characteristics: Vc,SDChVc,SDChVc,SDChVc,SDCh Vc,SDChVl_N,SDChInd_Ni,Vc,SDChInd_N1,1 IndIndIndInd The vector of certain value socio-demographic characteristic SDCh of specific certain web-community Vc: )U(Ind )U(Ind )U(Ind LKI Vc,SDCh Vc,SDCh Vc,SDCh 1,Vc,SDChInd_N 1,j 1,1 Vc,SDCh
- 9. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 7 Table 1 Tabular representation of functions: N_Vl & N_Ind SDCh N_Vl N_Ind Age 2 6 Gend 2 12 Edu 3 7 Sphere 3 11 To calculate the distance from the reference socio-demographic characteristics value to each possible socio-demographic characteristic value of atomic each web-community member we take as a basis the formula for determining the Euclidean distance: k,SDChInd_N 1i SDCh i 2 j,ij,i k j w*IndIndUser,Value U,SDChVc,SDCh where Vc,SDChVl_N1k ; SDCh iw - weight coefficient of particular lingvo-communicative indicator of particular value of socio-demographic characteristic. As a result we take such value of socio-demographic characteristic which corresponds k * min to the maximum value UValue . Moreover, the matrix ijIndLKI is universal for all values of socio-demographic characteristics of a particular web-community, for which are synthesized models. Depending on the subject and the type of web-community, the model is synthesized for each socio-demographic characteristic values using automated information system monitoring. The weight coefficients of lingvo-communicative indicators are presented in the vector: SDCh,Vl Vc,SDChInd_N SDCh,Vl j SDCh,Vl 1 SDCh,Vl wwwW The weight coefficient vector of indicators SDCh socio-demographic characteristics - Vl value, obtained as a result of automated information system monitoring. The importance of lingvo-communicative is indicated by weight coefficients. 3.2 Lingvo-communicative indicator weight coefficient determination The weight coefficient determination for lingvo-communicative indicators of all socio-demographic characteristic values for each socio-demographic characteristic is completed by using information system of multilevel computer monitoring. At the stage of the input data array forming of information system multilevel monitoring is processing information tracks
- 10. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 8 of web-community member for the presence of socio-demographic markers to form lingvo-communicative indicator sets for specific web-community with the same themes. The matrix of lingvo-communicative indicators is an array of input data for information system's multi-computer monitoring. The input data array of multilevel monitoring information system should meet certain requirements for the synthesis of qualitative multidimensional model and must be matrices of each marker of lingvo-communicative indicators frequency characteristics in each web-community member information track. It is the basis for the socio-demographic characteristics models synthesis in information system multilevel computer monitoring. 4. SOFTWARE FOR SOCIO-DEMOGRAPHIC PROFILE VERIFICATION OF WEB-COMMUNITY MEMBER The complex architecture reliability check of web-community member personal data by computer-linguistic analysis of the socio-demographic characteristics reliability of web-community member is developed, also is described the main components of the complex, their functions and technical aspects of implementation. Selecting the virtual community and information track of community member Analysis of information track Formation of socio- demographic profile Checking the reliability of the results of the verification process of socio-demographic characteristics Determination of membership level to a socio-demographic characteristics Determination of the socio- demographic characteristic values Determination of adequacy of account personal data Saving the socio- demographic profile Figure 2. The scheme of functioning of "Socio-demographic profile verifier"
- 11. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 9 The developed system of sets of web-member Internet communication lingvo-communicative indicators is the basis for software of test socio- demographic characteristic values of web-communities members - "Verifier of socio-demographic profile". The scheme of software algorithm "Verifier of socio-demographic profile" is described in Figure 2. The algorithm of "Verifier of socio-demographic profile" is presented in the following stages: Step 1. Selecting the web-community and information track of member. Step 2. Analysis of information track. Step 3. Formation of socio-demographic profile. This step included two stage: determination of the socio-demographic characteristic value and determination of membership level to a socio-demographic characteristics. Step 4. Checking the reliability of the results of the verification process of socio-demographic characteristics. Step 5. Determination of adequacy of personal account data. Step 6. Saving the socio-demographic profile. The result of this step is the creation and preservation of socio-demographic profiles of web-members. 5. DETERMINATION OF THE ACCOUNT PERSONAL DATA ADEQUACY OF WEB-COMMUNITY MEMBER Adequacy of account personal data - is the characteristic of account personal data which indicates results reliability degree of the verification process of socio-demographic characteristics of a particular web-community personal data that is specified in correspondent account, that is, the determination of the account personal data veracity. The measure of the adequacy of account personal data - a certain level of probability that is analyzed by computer-linguistic analysis of web- community member account to reference web-community member account based on real and relevant information about web-community member. The difference between 1 and User,Valuek j - is the distance between the reference socio-demographic characteristics value and k-th web-community member atomic socio-demographic characteristic value that is determined as an adequate account personal data of k-th user. User,Value1User,Value k j k j where User,Valuek j - the distance from the reference socio- demographic characteristics value to each possible socio-demographic characteristics value of atomic k-th web-community user:
- 12. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 10 k,SDChInd_N 1i SDCh i 2 j,ij,i k j w*IndInd1User,Value U,SDChVc,SDCh where Vc,SDChVl_N1k . Moreover, 1,0User,Valuek j . This vectoring method consists of the data transformation in the vector form that will allow determining the extent of similarity between the socio- demographic characteristic values. The similarity measure value between the socio-demographic characteristics value and control vector (the value that is determined in training selection of web-forums members for each set of socio-demographic characteristic values) indicates a web-community member identity to a certain socio-demographic characteristic value. The analysis results vary according to the web-community specificity. To greater ratio value corresponds the more important linguistic-communicative indicator for the verification of socio-demographic characteristics in particular web-community. 6. RELIABILITY OF THE VERIFICATION PROCESS RESULTS The reliability of the result of the socio-demographic characteristics verification of web-community member allows to evaluate the effectiveness of computer-linguistic analysis of web-community member’s content and to construct the socio-demographic profile of the web-community member for web-community management and to consider this figure in web-community moderating process. Reliability of the results of the socio-demographic characteristics verification - is a composite index, which depends on the following parameters: the level of account filling, content topicality, and the relevance of personal data in the account, the technical correctness of filling the account, the administrative authority and web-community member activity. Reliability of the results of the socio-demographic characteristics verification calculated by the formula: User 8 User 7 User 6 UAc 5 User 4 Cont 3 UAc 2 UAc 1 AnkRCBkActvkTechCkAdmP kActlkActlkComplk)RRVer(SDCh where 821 k,,k,k – the weight coefficients of each parameter of the reliability of the verification process results, which are determined by the member’s communicative behavior and web-community development scenario, with 1k i i , 0ki ; UAc Compl – the level of account filling; UAc Actl – the relevance of personal data in the account; Cont Actl – the level
- 13. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 11 of content topicality; User AdmP – the administrative authority; UAc TechC – the level the technical correctness of filling the account; User Actv – the level of activity; User RCB – the level of compliance with the web-community member rules; User An – the level of anonymity. As a result, 1,0)RRVer(SDCh . Determination of the reliability level of the result of the socio-demographic characteristics verification: 0,75 < Reliable Result ≤ 1; 0, 25 < Ambiguous Result ≤ 0,75; 0 ≤ Simulate Result ≤ 0,25. 7. CONCLUSIONS Determination of the account personal data adequacy of web-community member is the important scientific and applied problem. The construction methods and means of basic socio-demographic profiles validation of web- communities members by computer-linguistic analysis of web-members information track is solved this problem. The system of lingvo-communicative indicators involves the content creation and processing of training selection of web-forum members is formed. Weight coefficients of lingvo-communicative indicators are determined. The matrix of linguistic-communicative indicators is formed. The software algorithm of web-community members' socio-demographic profile verification – "Verifier of socio-demographic profile" is designed. Computer-linguistic analysis of information track of Ukrainian web-forum members for grammatical, lexical-semantic and lexical-syntactic features are more specific to one particular socio-demographic characteristic value of certain web-community members. The research results are significantly affected by messages context and discussion topics. The basis of this study is a diverse sample of user information tracks of all thematic chapters, more than 40 Ukrainian web-forums. Determination of socio-demographic markers is performed by analysis of information track of more than 640 members of Ukrainian web-communities. The study equally considered web-forum discussion that arises from a variety of interests of young persons and adults, men and women with different levels of education. The reliability of the result of the socio-demographic characteristics verification of web-community member allows to evaluate the effectiveness of computer-linguistic analysis of web-community member’s content and to construct the socio-demographic profile of the web-community member for web-community management in web-community administrating process.
- 14. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 12 8. REFERENCES [1] Fedushko, S., Syerov, Yu., 2013. Design of registration and validation algorithm of member’s personal data, International Journal of Informatics and Communication Technology, Vol.2, No.2, pp. 93-98. [2] Shakhovska, N., 2011. Methods of customer data processing using intelligent agent of data sources structure determination. Actual Problems of Economics, Vol. 7(120), pp. 338-346. [3] Fedushko, S., Peleschyshyn, O., Peleschyshyn, A., Syerov, Yu., 2013. The verification of web-community member's socio-demographic characteristics profile, Advanced Computing: An International Journal, Vol.4, No.3, pp. 29-38. [4] Syerov, Yu., Peleschyshyn, A., and Fedushko, S., 2013. The computer-linguistic analysis of socio-demographic profile of web-community member. International Journal of Computer Science and Business Informatics, Vol. 4, No. 1, pp. 1-13. [5] Shakhovska, N. and Syerov, Yu., 2009. Web-community ontological representation using intelligent dataspace analyzing agent. X-th International Conference "The Experience of Designing and Application of CAD Systems in Microeletronics", Polyana-Svaliava, Ukraine, pp. 479–480. [6] Shakhovska, N., 2011. Consolidated processing for differential information products. VII-th International Conference "Perspective Technologies and Methods in MEMS Design", Polyana-Lviv, Ukraine, p. 176. [7] Fedushko, S., Bardyn, N., 2013. Algorithm of the cyber criminals identification. Global Journal of Engineering, Design & Technology, Vol. 2, No. 4, pp. 56-62. [8] Korzh, R., Peleschyshyn, A., Syerov, Yu., and Fedushko, S., 2014. The cataloging of virtual communities of educational thematic. Webology, 11(1), pp. 1-16. This paper may be cited as: Fedushko, S., Syerov, Y., Peleschyshyn, A. and Roman, K., 2015. Determination of the Account Personal Data Adequacy of Web-Community Member. International Journal of Computer Science and Business Informatics, Vol. 15, No. 1, pp. 1-12.
- 15. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 13 Layered Defense Approach: Towards Total Network Security Kalaivani Chellappan Department of Electrical, Electronic and System Engineering Faculty of Engineering and Built Environment, UKM, Malaysia Ahmed Shamil Mustafa Department of Electrical, Electronic and System Engineering Faculty of Engineering and Built Environment, UKM, Malaysia Mohammed Jabbar Mohammed Department of Electrical, Electronic and System Engineering Faculty of Engineering and Built Environment, UKM, Malaysia Aqeel Mezher Thajeel Department of Electrical, Electronic and System Engineering Faculty of Engineering and Built Environment, UKM, Malaysia ABSTRACT Computer network security is one of the most critical issues facing different business organizations. Protecting organization’s data - which is the core of the organization existence- against attacks is very important. Multiple security tools should be implemented in the same time in order to protect this data, as modern attacks can easily bypass most single operated security systems. A well designed security system which take into considerations most possible network threats is necessary to prevent intruders and provide secure data exchange. In this paper, layered defense approach is presented as a best solution to build network security system. In this approach multiple mechanisms are used together to keep high security level. Keywords: Network security; layered defense approach; risk analysis; computer network attacks. 1. INTRODUCTION Growing number of computer networks and recent developments in information technology have led to increased demand on network security issues. Although it’s huge benefits such as shared data usage, network convergence introduced large amounts of threats to the organization’s network systems. Having more data flowing through the network poses security risks for both the facilities and IT teams, as a result a more complex protection schemes should be applied. Providing protection for both hardware and software components of the network is not a single person responsibility, the cooperation between IT
- 16. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 14 staff and the system is required to achieve network protection against attacks [1]. As different staff members have different responsibilities, different roles should be assigned to them when building the secure network. To provide a secure network design, an analysis of possible threats should be carried out. Appropriate risk analysis can provide an outlook on possible network threats, network vulnerabilities and the best mechanisms to maintain and mitigate these effects. Different security mechanisms can be implemented to secure any organization’s network beginning from the core network and ending with securing user end point. However, some vulnerable point could be missed which can easily provide a base to attack the network. Well-designed security system can guarantee high security level which is required especially in protecting data. The essential approach towards high level network security is layered defense. Layered defense is defined as the concept of protecting a computer network with a series of defensive mechanisms such that if one mechanism fails, another will already be in place to thwart an attack [2]. Because of the variety of attacks, no single technique can successfully protect the network. By Utilizing layered defense strategy [1], any attack can be prevented or at least detected. This approach requires deep coordinates between users and network resources in order to assure secure data exchange. Rather than dropping few firewalls between network or installing additional malware detection software, layered defense implementing multiple strategies which are divided into different layers. Each layer introduce partial defense technique against specific attack, once the layer defense is passed, next layer defense should be able to mitigate the attack or at least detect it. Like any other security system design, layered security requires a deep analysis of the attacks in order to identify which mechanisms to employ and where. Figure 1 shows the basic steps to design a security system. In this paper, we introduce layered defense approach to provide total network protection. The paper is organized as follows: section 2 explains the most famous attack on computer networks, in section 3, we discuss the importance of risk analysis in building network security system. Section 4 introduces detailed layered defense approach, finally section 5 contains the conclusion on our work. Figure 1: security design steps.
- 17. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 15 2. ATTACK CLASSIFICATION The common known attacks can be classified as follows [3, 4]: A. Eavesdropping or packet sniffing In this case the attacker captures each packet flows across the network with the aid of packet sniffer application program. Without strong encryption, the captured packed is plain text which simply reveal networks information [5]. B. Data modification The attacker aims to modify the content of the captured packet without the knowledge of the sender or the receiver. C. IP address spoofing This attack enables the attacker to access network data, modify it or even delete it [5, 6]. D. Password based attacks Once the attacker discloses the user’s password, he can access user’s data and has all the rights and privileges as real user. All previous attacks will result in some data being stolen or modified, anyway the network can continue work properly. When the attacker is more violent, it will develop more dangerous attacks which will lead not only to network data changed, but also to destroy the network and bring it down [6]. Once the attacker captured any network node, the node is said to be compromised. In this case the attacker can start a second group of network attacks which contains: A. Trust exploitation As devices in the shared environment should trust the information from each other, an attacker can use the compromised device to send and modify information as a trusted user. B. Port redirection By installing port redirection software like NetCat on the compromised device, the attacker can redirect packets to another port. In this case, all network data including IP addresses, passwords and other important information can be monitored by the attacker. C. Man in the middle attack In this attack, all packets exchanged between two users is passed through the compromised device. The attacker could modify the packets without being noticed by the sender or receiver. D. Denial of service
- 18. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 16 By flooding the network with extra traffic, the attacker aims to prevent the network from performing its job. For example, the attacker can flood the server with so many requests which makes it take a long time to process these request and become unavailable for other users. DoS attacks are the hardest attacks to mitigate as they are performed using the allowed traffic in the network [7]. E. Malicious software (Viruses, worms and Trojans) Once the attacker becomes trusted within the network, he can send packets contains viruses, worms and Trojans to different network devices which will deal with the data as trusted data. These malware can affect devices in different ways, starting from erasing files to run arbitrary codes causing memory overloading, consequently switch of the device. F. Network partitioning Using port redirection attack and packet sniffing, the attacker can redirect all the packets to flow to certain device which is basically compromised. In this case, a lot of network nodes (devices) will be virtually out of the network, which can a virtual network partitioning. 3. RISK ANALYSIS The first step towards building a secure network, is to carefully identify and analyze each attack and evaluate the risks introduced to the organization's network by these attacks. Risk analysis helps to define possible damage caused by the attacker and methods to mitigate this damage or even prevent it. The basic methodology of risk analysis can be summarized as in [8] Identify the assets. Identify the threats. Identify the vulnerabilities. Identify the existing controls Generally, previous four points can be seen as three short questions; what to protect, from whom and how. Assets identification should be done first in order to define what asset to protect. Network asset contains both hardware and software components. Risk analysis should clearly define which asset to be protected and what level of protection required. After that, the organization should define the possible threats to its network. Threats contains every unwanted events that can damage the assets, and can be triggered by natural or human action. Identification of threat sources also is important point, threat sources varies from natural, human or environmental hence, good identification of threat source should be done even before building the network architecture. Network vulnerabilities can be defined as” a flaw or weakness in system security procedures, design, implementation, or internal controls that could be accidentally triggered or
- 19. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 17 intentionally exploited and result in a security breach or a violation of the system's security policy” [9]. The vulnerable points in the network will not cause any harm unless some threat exploit to it. All vulnerabilities should be well identified and monitored to detect any threat possibilities. The final stage in risk analysis is to identify the existing controls. Controls mean all existing procedures and mechanisms to mitigate the vulnerabilities. Existing controls can be identified with the help of documentation of controls and plans of risk treatment implementation. Multiple controls should be assigned to mitigate every vulnerability, if one control failed, a complimentary controls should be addressed to mitigate the threat. Risk analysis can be done in two ways: Quantitative and qualitative [8]. Quantitative risk analysis is used to define the probability of risk occurrence and possible losses, and assign them numerical values. Quantitative analysis helps to estimate the assets, build cost, protect cost and repair cost. Qualitative analysis is used to predict the level of protection required to the network including asset and applications. Qualitative analysis represents the initial monitoring to identify risks and threats that need deeper analysis, and if the numerical threat estimation is required. 4. LAYERED DEFENSE APPROACH Layered defense is defined as a set of network defense procedures and technologies which aims to protect the network from intruders, these techniques is organized such that if one failed to protect, the next one will be ready to replace it. The complexity of the procedures depends on organization requirements in terms of security level, cost and operability. Any network security approach should be designed according to the organization’s security policies which is defined as “a formal statement of the rules by which people who are given access to an organization’s technology and information assets must abide” [10]. In order to design a secure network, it is really important to have a strong security policies. The first step in security policies is to inform the network users how to protect information and technology assets. Dividing people between network administrators and users can help to protect the network by definition of limited access. Also setting passwords for certain devices, information or application will effectively protect the data from unwanted access. In general, security policies can be summarized as: what to protect, why, from whom and who is responsible for this protection procedure [11].
- 20. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 18 The layered defense approach is described in terms of defense layers which can be seen in Figure 2, these layers are as follows: First layer: Perimeter defense; which contains conventional procedures like firewalls, malware detection software and network monitoring software. Second layer core network defense using network monitoring, server end point protection and patching. Third layer: host defense such as desktops, mobiles and laptops devices. Fourth layer: applications defense, which contains both applications run on end user devices and applications run on dedicated servers. Fifth layer: data defense, which is the main target of any security system. A. Perimeter defense Networks perimeter is the point where network connects to the outside so called untrusted networks, hence providing secure perimeter is the first step to prevent unwanted access to the network and so the system information. According to Microsoft TechNet the perimeter is defined as “every point where the internal network is connected to networks and hosts that are not managed by the organization’s IT team.” The firewall is the base of every Figure 2: Layered defense approach.
- 21. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 19 good configured perimeter. As firewall is the security guard which controls the entry points of the network by checking every incoming and outgoing packet, a set of rules should be predefined by the organization to help configure the firewall properly. In this case, well configured firewall will be able to decide what packets to accept and what to discard. According to [12] two categories of firewalls exist; state-less firewalls and state-full. If the firewall tested the fate of the packet by examine the packet itself, then it is called state-less. But if the decision is made not only based on the packet test but also by looking to the previous accepted packets, then it is called state-full. As the packet flow is controlled, many harmful effects can be eliminated keeping the network safe. B. Core network defense The basic key for core network protection is the good designed architecture. DMZ which is network area separating between firewall and the first router in the network is an important defense tool. DMZ hardware is working as the second check point for the packets, by fragmenting the packet, DMZ can detect whether the payload is malicious or not. Figure 3 illustrate the implementation of the DMZ within the core network. Intrusion detection and prevention systems IDPS forms the second defense line in securing the core network. By collecting information from different network sources, these systems can detect possible threats [13]. For example, when the attacker performs port redirection attack, most of the Figure 3: DMZ implementation to protect the core network
- 22. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 20 data flows to the compromised device. By analyzing the traffic in the network, IDPS can find the threat and report to the system administrator to take proper reaction. The secondary router in the system is also involved in the layered protection [14]. By dividing the network into different working groups (VPNs), the secondary router can disseminate the network traffic in to proper working groups. C. End point defense The end point in the network could be both user’s device and servers. User’s information can be protected by the mean of operating system protection by adjusting security configurations. Other procedures could be useful too such as closing unused ports, hard disk encryption and application whitelisting. Host intrusion detection systems is also can be used to protect hosts from outside attacks. Anti-viruses software protects the device from malicious software. These software manages databases which contain signature for all known malicious computer codes and use signature scanning to define malicious files. By detecting these file, many attacks and threats can be omitted. D. Application defense Many attacks target the applications especially those which run on the server. Some of these attacks are; buffer overflow attacks, password guessing attacks, directory traversal attacks, and poorly configured network applications that expose data to unauthorized users. Most client applications do not listen to network ports, so they usually are not susceptible to remote network attacks. Different tools and solutions could be used to protect applications like Internet Information Services hardening and SQL hardening for protecting servers [15], also installing applications and their updates should be done from their original vendors. E. Data defense As business data is the most valuable content of any organization, providing data protection is the main goal for any network security system. Adding to previous mechanics, data defense could be done by controlling the access to files and folders using access control lists (ACLs) [16], besides using some encryption techniques. To prevent data loss, data back up or restore should be done periodically using CDs or external hard disk. Finally saving data on external hard disks rather than keeping it on desktop device can also protect it from being stolen. Generally, the layered defense approach use multiple techniques together to provide total security. For example; an attacker who has physical access to the network’s computer has to gain authorization to access the data. As the access is protected by user’s password, the attacker should gain this password first. Once the attacker break first defense layer (the password),
- 23. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 21 second defense layer – in this case, it could be hard disk encryption- will be ready to defend the attack. If the attacker succeed to break the encryption, next defense layer – let’s say; host based intrusion detection system (IDS) - can detect the attack, by comparing attacker behavior with system logs. The intrusion detection system will report the attack to the administrator to take the proper reaction. 5. CONCLUDING REMARKS In this paper, we introduced a layered approach for computer network security. The layered network defense can provide better security level by the mean of arranging defense mechanism in consecutive layers such that each mechanism has less attacks to deal with compared with the mechanism in previous layer. Different security mechanisms are required to be implemented in order to provide total network protection which increase the cost and complexity of security system. Anyway, a good risk analysis of the organization network can reduce the cost of implemented security mechanisms by predicting which mechanism to apply and at which layer. REFERENCES [1] Banathy, A., Panozzo, G., Gordy, A. and Senese, J., 2013. A Layered Approach to Network Security, indestrial IP database, available at :< http://www.industrial-ip.org> [accessed 15 November 2014]. [2] Shenk, J., 2013. Layered security: Why it works, SANS institute reading room database. availabel at: < http://www.sans.org/reading-room> [accessed 15 November 2014]. [3] De Capite, D., 2006. Self-Defending Networks: The Next Generation of Network Security, Cisco press, NewYork. [4] Kumaravel, A., 2013. Multi-classification Approach for Detecting Network Attacks. IEEE conference on information and communications technology ICT, Jeju island, April 11-12 2013. Available at:<http://www.ieeexplore.com>, pp.1114-1117 [accessed 12 December 2014]. [5] Orebaugh, A. and Pinkard, B., 2008. Nmap in the Enterprise: Your Guide to Network Scanning. [e-book] Syngress press. available at: <http://www.amazon.com/> [accessed 03 December 2014]. [6] Harris, J., 2002, Cisco Network Security Little Black Book. [e-book] Paraglyph press. available at: <http://www.amazon.com>[accessed 17 December 2014]. [7] Hsu, F. H., and Chiueh, T., 2008. Scalable Network-based Buffer Overflow Attack Detection, IEEE Xplore database, available at: <http://www.ieeexplore.com>, pp.163- 172, [accessed 10 December 2014]. [8] International Standards Office, 2011. BS ISO/IEC 27005-2011, Information technology- Security techniques- Information security risk management: Electronoic documents. ISO. available at:<http://www.iso.org> [accessed 21 December 2014].
- 24. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 22 [9] Stonebumer, G., Goguen, A., and Feringa A., 2002. Risk Management Guide for Information Technology Systems, National Institute of Standards and Technology e- library, available at:< http://www.nis.gov>, p.54 [accessed 23 December 2014]. [10] Fraser, B., 1997. Site Security Handbook, RFC 2196, available at:<http://www.ietf.org> [accessed 10/12/2014]. [11] Malik, S., 2002. Network Security Principles and Practices. [e-book] Cisco Press. available at: <http://www.amazon.com> [accessed 23 December 2014]. [12] Gouda, M. and Liu, A., 2007. Structured firewall design, International Journal of Computer and Telecommunications Networking, Vol 51, Issue 4 ; pp1106–1120. [13] Beigh, B., Peer, A., 2012. Intrusion Detection and Prevention System: Classification and Quick Review, ARPN Journal of Science and Technology, Vol 2, No 7, pp.661- 675. [14] Conkil, WM. and White G., 2010. Principles of Computer Security: CompTIA Security+ and Beyond. 3rd ed [e-book] McGraw-Hill/Osborne Media, available at: <http://www.amazon.com>, [accessed 01 December 2014]. [15] Shucheng, Y. et al., 2010. Achieving secure, scalable, and fine-grained data access control in cloud computing, IEEE conference on computer communications, San Diego, Ca, March 15-19 2010. Avaialbel at <www.ieeexplore.com>, pp. 1-9, [accessed 07 December 2014]. [16] Huu, T. et al., 2005. A trust based access control framework for P2P file-sharing systems, Proceedings of the 38th Annual Hawaii International Conference on System Sciences. Hawaii island, US, January 3-6 2005. Available at: <http://www.ieeexplore.com>, pp. 1-10, [accessed 16 December 2014]. This paper may be cited as: Chellappan, K., Mustafa, A. S., Mohammed, M. J., and Thajeel, A. M., 2015. Layered Defense Approach: Towards Total Network Security. International Journal of Computer Science and Business Informatics, Vol. 15, No. 1, pp. 13-22.
- 25. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 23 Millennials: Entitled Networking Business Leaders Dr. Caroline Akhras Associate Professor, Notre Dame University ABSTRACT Millennials are the young emerging workforce. Virtual workplaces led by young business leaders are replacing the brick and mortar leaders in the developed world. In the global marketplace, local, regional, and multinational firms delegate virtual business leaders to address company transactions. An essential component in the competitive global environment, millennial business leaders may shape comparative advantage, especially in the Middle East and North African Area (MENA). This case study focuses on the emergence of millennial leadership inside virtual teams. The aim of this paper is twofold: (1) whether the organizational structure impacts millennials’ authority as the team leader and (2) whether structure influences the team members’ perception of their leaders’ entitlement attitude. Participants were selected and teamed up as virtual business units. From the research analysis, it was found that millennial leaders emerge from business units Moreover, leaders may use authority and may have an entitlement attitude. Recommendations were made based on the results and implications. Keywords: Leadership, Millennials, Entitlement, Authority, Virtual Communication 1. INTRODUCTION Millennials, technology, and organizational structures are focal in third millennium business management, especially critical in the Middle East and North African front given globalization, liberalization, and emerging democratization. Research has found that millennials are the young emerging workforce; they are entitled; and they network 24/7. Studies have found that young entrepreneurs have played a vital role in shaping Middle East and North African (MENA) business growth: Between 2002 and 2010, foreign investment exploded in the Arabian Gulf influencing the industrial and organizational climate (Kalayci and Adtan, 2012; Toone, 2012). Millenials are said to be energized and technologically adept as a human resource, using social media to network business objectives. Nonetheless, effectively leading and managing a business is challenging, whether interacting face-to-face or online, especially when the business leader is neither sufficiently experienced nor assigned but emerges. Furthermore, millennial business leaders who exploit fast-changing opportunities may require a different range of core competencies than those in traditional structures given their sense of entitlement.
- 26. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 24 2. RELATED WORKS Studies have shown that business leaders’ awareness of rapidly changing environments teeming with opportunities and threats generate competitive survival strategies. Many traditional business organizations seem to be eroding, defunct, bringing with them high uncertainty avoidance and resistance to adapt, yet millennials are change agents as leaders in the international marketplace in which multinational business strategy implements procedure using broader flatter organizations. New structural design mechanisms are built to ensure leaner more flexible coordination and control (Maney, Hamm and O’Brien, 2011; Goleman, 2006; Drucker, 1996). The opportunities for and need of virtual organizations has grown with the combination of increasing globalisation and widespread developments in information communication and technology (ICT) (Hill and Hernandez_Requejo, 2011). For those who are flexible enough to create, innovate, adapt and/or engage in change management, opportunities for business growth and development abound (Kinicke and Fugate, 2012; Kets De Vries, 2010; Beaver and Hutchings, 2005; Farren and Kaye, 1996; Drucker, 1985). Millennial executives as virtual business team leaders look for methods and tools that can help them sustain competitiveness; many are able to reinvent themselves. Research studies have shown that millennials leaders understand that today’s organizations whether traditional or decentralized, bureaucratic or boundaryless (Welch and Welch, 2007) are networks (Shirky, 2008; Handy, 1996) much more than a structure to be quantitatively designed, measured, and controlled. Young yet versatile with a mindset that is open rather than closed to the “inner and outer sphere (Goethe),” Millennials generate organizational structures that require both or either of a forceful or enabling leader contingent on the context and the emotional economy (Kellerman, 2010; Kaplan and Kaiser, 2006; Goleman, 2006). One of the most common changes made in organizations is the development of teams (Robbins, 2011; Elloy, 2008; Osburn and Moran, 2000) whereby virtual teams are groups of employees dispersed in time and geography who, collaboratively through interdependent work tasks, generate a product/service using ICT (Zivick, 2012). Researchers note that virtual leaders must develop a strong portfolio of technical, interpersonal, and conceptual skills appropriate for managing the virtual organizational structure (Bass and Bass, 2010) whose framework is quite similar to traditional ones though supported and driven by online leadership. Moreover, research studies have also shown that in a leaderless autonomous work team context leadership behaviour is necessary to move the team forward (Zigurs, 2003). Reliance on a leader who “emerges” is essential for the team as the “leader” seems to “fit” the responsibilities: in addition,
- 27. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 25 she/he is selected because of proven competence (Erez, Lepine and Elms, 2002). Studies have shown that whether assigned or emergent, leadership, mediated by technology, implements the same tasks/performances and builds the same relationship functions online as traditional organizations do though due to availability of information, dispersion of the team, and permanence of the communication some differences exist (Avolio and Kahai, 2001). Research has shown that team functional issues as task completion may be more difficult to resolve. In addition, studies showed that use of authority is at times used laterally rather than hierarchically (Glucker and Schrott, 2007).Virtual leaders may have additional issues to handle stemming from the online context (Nicholson et al., 2007). Millennials are the emerging workforce. Born between 1980 and 1999, they are educated, sociable, civic-minded, have a sense of morality and diversity, are well-travelled, and technologically sophisticated (Pew Research Center, 2010; Brokaw, 1998; Strauss and Howe, 1991). They are independent, hard working, and entrepreneurial. These personality characteristics were shaped by the first fifteen years of the millennials’ life that served as the foundation for their expectations and impacted their behavior. The new leader on the business frontlines is less process and outcome oriented and less money focused. Millennials balance family life with their work life, a witness of and probably a testament to their parents being downsized. Their world is wired and connected: computers, cell-phones, I-pods, I-pads, DVDs, and cable TV. Having grown up with technology, this generation has an ICT confidence and tenacity unlike others, awakened by and aware of world events 24/7 (Akhras, 2012a). More importantly, millennials want to be challenged in life and at work; easily bored with routine streamlined work processes (US Department of Education). This Spawned Generation, Generation Whatever (Christen in Payment, 2009, p.23) may seek creative challenging tasks, working perseverant and consistently to win (Crampton and Hodge, 2007), mainly driven by personal concerns. Research has shown that millennial, like all other generations, may have issues that need to be resolved, chief among which is their sense of entitlement: They perceive themselves as the first, and they must consistently be considered as the first (Twenge, 2006). Studies have found that millennials’ entitlement is related to their socialization and their level of their internet connectivity and networking dependency. Although brought up by different generations of parents, research has shown that similar parenting and socialization skills enriched millennials: children were expected to excel and have a high sense of achievement. Promoting self- esteem was part of their elementary education; moreover, parents also excessively praised childrens’ assignments (Trzesniewski and Donnellan,
- 28. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 26 2010; U.S. Department of Education). Millennials’ childhood was highly scheduled with choice-overload and resultant stress-overload (Gleeson, 2007), maybe they are better seen as an Accelerated Generation. Entitlement in the work environment may also have sprung from the fact that millennials have been socialized in a world of instant information and social networking 24/7 where events are celebrated round-the-clock. As such, researchers have found that millennials thrive well in work-related- contexts supported by positive as well as continuous instant feedback (Demirdjian, 2012; Cisco Connected World Report, 2011; U.S. Department of Commerce, 2013; Scheck, 2012; Silbergh and Lennon, 2006). Moreover, it has also been noted that millennials tend to work well with others, collaborating, bringing to the work context, a de-cubiclized work space (Kapoor and Solomon, 2013; Zopiaris, Krambia-Kapardis and Varnavas, 2012; Lowe, Levitt and Wilson, 2008). Researchers have noted that not only do millennials search for and combine frequent positive open communication, but they also share it (Marston, 2007; Howe and Straus, 2007). Millennial leaders play a critical role in MENA business world. Given the review drawn from the literature, this research study seeks to determine whether the organizational structure impacts millennials’ authority as the team leader and whether being “virtual” influences the team members’ perception of their leaders’ entitlement attitude in both the assigned-leader and the emergent-leader teams. 4. METHODOLOGY This section covers the purpose of the study, the research questions, the participants, the procedures used in the study, the research design, rubrics, and analysis of data used. Purpose The purpose of this study is to determine whether the organizational structure influences team members’ perception of their leader’s application of authority and their entitlement attitude. Research Questions o Hypothesis One: In terms of online group transactions, virtual business team members with emergent leaders perceive significantly more authority being applied by the leader than do virtual teams with assigned leaders o Hypothesis Two: In terms of online group transactions, virtual business team members whose leaders emerge
- 29. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 27 perceive significantly more use of an “entitlement” attitude by the leader than do virtual teams with assigned leaders. Participants The participants who attend two graduate level business courses at the faculty of business administration and economics are selected as participants. The sum total of students is 60: 34 are male; 26 are female; and 31 work in domestic and international companies. All participants attend the Fall Semester at a private English speaking university in the Middle East and North African Area (MENA). Procedure In this research design, the participants are assigned a graded team project across the academic semester. The participants are placed in virtual teams of five members. Each team is to work on tasks on the internet. The team project is to be developed by all the members of the team who are to meet regularly on the team blog in order to achieve their assigned team objective. The blogs are generated by the course leader who is the blog administrator. During the sixth week of a fifteen week semester, the participants are placed in formal teams and told to meet to discuss the project and how and when they will work together. During the seventh week, the formal teams are divide into two categories: assigned team leader and no assigned team leader. Thus, three teams had an assigned leader (AL) and three did not. During the eighth week, the participants as virtual team members are told to collaborate on the blog, synchronously or asynchronously, in order to personalize their blog, adding IT features to enhance and facilitate online communication. During the ninth week, the participants are given the first task on the group project. This is to be performed by each team member, individually. The task is submitted on the team blog. During the eleventh and twelfth week of a fifteen week semester, the team participants have a collaborative task. All need to work together, synchronously or asynchronously, to complete the task. The second task must be submitted as one assignment online. During the thirteenth week, the final task is to be completed. The team participants are to finalize the graded team project. It is to be submitted online. During fifteen week, all the participants are to fill out a survey (See Appendix One).
- 30. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 28 The Research Design, Rubrics, and Analysis of Data The research is conducted as an experimental design with mixed method. Two main areas are probed—conditions that lead to the emergence of virtual business team leaders and comparative performance following the emergence of the leader. Rubrics were generated to measure each context. Data was analyzed using Levine’s test for equality of variance and independent t-tests. Rubric to Assess Perception of Authority The first rubric is paired three times with Hypothesis One-- In terms of online group transactions, virtual business team members with emergent leaders perceive significantly more authority being applied by the leader than do virtual teams with assigned leaders. On the Likert Scale (1 is non existence and 5 is regularly applied) points reflect the participants’ perception of the leader’s application of authority (see Figure 1 below). 1.0-2.0 points When leader is not perceived as applying authority. 3.0 points When leader is perceived as applying a moderate level of authority. 4.0-5.0 points When leader is perceived as regularly applying authority. Figure 1: Rubric to Assess Perception of Authority Application Rubric to Assess Perception of Entitlement: The second rubric is paired with Hypothesis Two which states that in terms of online group transactions, virtual business team members whose leaders emerge perceive significantly more use of an “entitlement” attitude by the leader than do virtual teams with assigned leaders. Thus, the rubric evaluates the attitude of entitlement reflected by the virtual business team leader’s on the Likert Scale (1 is non existence and 5 is regularly applied) (see Figure 2 below).
- 31. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 29 1.0-2.0 points When the leader is perceived as not having an attitude of entitlement. 3.0 points When the leader is perceived as having the inception of an attitude of entitlement. 4.0-5.0 points When the leader is perceived as having an attitude of entitlement. Figure 2: Rubric to Assess Perception of Entitlement 5. RESULTS Based on the data analyzed, the section below discusses the results of the analysis in line with the literature reviewed. The first hypothesis which stated that in terms of online group transactions, virtual business team members with emergent leaders perceive significantly more authority being applied by the leader than do virtual teams with assigned leaders was supported: three different tasks that were performed by the six virtual teams were evaluated ( Task One: T=2.834 df (36), Sig(1 tailed)=0.004<0.05; Task Two: T= 2.408,df(58), Sig(1 tailed)+0.0095<0.05; Task Three: T=7.405, df(30), Sig (1 tailed)+0.000<0.05) (See Appendix One). Emergent leaders played a dominant role: They stepped forward to take over and directed the team to success (See Figure 1: Rubric to Assess Perception of Authority Application). The MENA Millennial leaders held themselves responsible to ensure the tasks were completed in terms of path and alignment while others in the team were responsive to being led as has been noted by other practitioner-researchers (Oh, 2012; Blanchard, 1996, p.86; Covey, 1996, pp. 152-3). Business leaders held the four members in their team accountable for their performance. In the six teams, the level of contribution of different members was not of equal measure meaning that in three of the teams, a team leader emerged applying authority to promote performance, communication, and interdependence while in the other three teams the assigned leaders directed performance. Virtual leaders have to consistently deal with maintaining hierarchical order and compliance online (Zivick, 2012). In the United Arab Emirates, teams have been a key component in delivering strategic goals in successful project-based companies where it was found team leaders and members played a responsible role in task performance (Randeree and Ninan, 2011). Tasks may need to be executed in a coordinated fashion for project completion (Kinicke and Fugate, 2012), and the interrelationship
- 32. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 30 between leadership and virtual teamwork and the members themselves was necessary in the six virtual teams (Carte, Chidambaram and Becker, 2006, p. 340). Studies show virtual teams need leaders with skills and personalities able to handle identical work-related problems online in a manner at times different from traditional co-located teams ( Avolio and Kahai, 2001). In this study, e-mail, mobile texting as well as face-to-face interaction were used as channels of communication. Similar to leaders in traditional teams, the face-to-face conversation on accountability may need to be done in a one-to-one manner using teleconferencing or video-conferencing (See Appendix One). When the leaders authoritatively directed, the team responded and the project was completed: In effect, emergent leaders applied more authority in each of the three tasks. The second hypothesis which stated that in terms of online group transactions, virtual business team members whose leaders emerge perceive significantly more use of an “entitlement” attitude by the leader than do virtual teams with assigned leaders was supported (T = 7.450, df (30) , Sig (1 tailed) = 0.000 < 0.05 level of significance) (See Appendix One). Within the three teams who were not assigned a team leader, the emergent team leaders were perceived as entitled (See Figure 2: Rubric to Assess Perception of Entitlement). Research studies have found that Millennials eschew linear trajectory (Gillespie, 2012), taking advantage of an opportunity to be “the trophy on the shelf.” The most entitled Millennial seems to have stepped forward and led the team as was noted by team members (See Appendix One). The leaders’ sense of self-esteem may have played a role as has been noted in other research studies (Trzesniewski and Donnellan, 2010; U.S. Department of Education). In this study, the leaders wanted to be challenged at work. Mundane work bores the Millennial leader (Edmonds and Turner, 2005). The Spawned Generation craves challenging tasks and is driven to win (Payment, 2009, p.23: Crampton and Hodge, 2007). Some of the emergent leaders may have tried to “de-cubiclize” the work space (Kapoor and Solomon, 2013; Zopiaris, Krambia-Kapardis and Varnavas, 2012), when they livened up the blog by adding IT features to it or when they sent supportive emails or mobile-texts to the members of the team (See Appendix One). As such, the Millennials, as the emergent business leader in their virtual team, worked in their own way to generate a work-related- context supported by positive as well as instant feedback (Demirdjian, 2012; Cisco Connected World Report, 2011; U.S. Department of Commerce; Silbergh and Lennon, 2006).
- 33. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 31 In short, the business team leaders in this study using information media understood that not all team members are as goal oriented or entitled as they. Given their need to excel, authority, mainly as a hierarchal tool rather than a lateral tool, was used to achieve assigned team directives issued by top level managers superior to them on the chain of command. Different technological channels of communication were tapped into to ensure team objectives were performed. 6. CONCLUSIONS Two conclusions were arrived at as a result of the study: virtual business team members perceive that their leaders apply authority to ensure that team goals are met; moreover, virtual business team members perceive their leaders as entitled, full of self-esteem, confident in their competence and their precedence in the business team. The research study found that some of the Millennials also known as MySpace Generation, dot.com Generation, the Internet Generation, the Great Generation, Generation Y, the “Yes” generation, Nexters, and the Digital generation may be perceived as entitled business leaders. They are comfortable in a flexible virtual work-related environment which they perceive as boundaryless (Welch and Welch, 2007). There, they network 24/7, at times applying authority to achieve team objectives. Millennial business leaders in the Middle East North African Area (MENA) today may be seen as enthusiastic, engaged, inclusive, sociable, achievers, and curious as other Millennials are (Pew Research Center, 2010; Everett, 2011; Lippmann, Bulanda and Wagenaar, 2009). The limitations found in the research conducted may have stemmed from the sample selected as it was a convenience sample (Fraenkel and Wallen, 2006). The generalizability of the findings is limited given the absence of random sampling as well as similar nationality, field of specialization, and uneven gender distribution. The student sample was composed of more males to females. An additional limitation was the sample’s lack of personal access to the internet as the factor of expense is an overriding issue in some developing countries. For those participants who had access, the lack of efficiency, speed, and intuitiveness of local digital services may be perceived as another limitation imposed on the sample in terms of their tolerance to the poor quality of the IT service. These factors have been observed by other practitioner researchers as obstacles to participants’ performance (Akhras, 2012b; Jenkins, 2006). To conclude, this small scale research study found that young leaders proved to be effective manager by applying authority. Pragmatically,
- 34. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 32 organizational culture proved to be hierarchical. Nonetheless, globalization, liberalization, democratization are changing the make-up of the political economic landscape as direct investment through multinational business corporation may infuse Western culture (Praveen Parboteeach & Cullen, 2012; Toone, 2012; Kalaycı and Adtan, 2012; Hill and Hernandez_Requejo, 2011). As a practitioner-researcher, I believe that further research ought to be conducted in other business institutions in the MENA in order to determine whether the finding arrived at in this small scale study (Bates, 2005) are similar to others in the region. It is recommended that further research be conducted in order to better understand the nature and role of millennials as the emergent or assigned new generation of post-information technology leader. REFERENCES Akhras, C., 2012a. Building student engagement: Integrating the discussion forum. Journal of Emerging Trends in Computing and Information Sciences, 3(10). Akhras, C., 2012b. MBA online: Is challenging peer work motivating? Mastered? Journal of Educational Multimedia and Hypermedia, 21(4), 215-231. Alexander, C. S. and, Sysko, J. M. 2012. A study of the cognitive determinants of Generation Y’s entitlement mentality. Academy of Educational Leadership Journal, 16(2), 63-68. Avolio, B. J. and Kahai, S. S.,2001.Adding the e to e leadership: how it may impact your leadership. Organizational Dynamics, 31(4), 325-338. Bass, B. M and Bass, R. 2008. The Bass Handbook of Leadership: Theory, Research, and Managerial Applications. New York: Free Press. Bates, A. W. 2005. Technology, E-Learning and Distance Education. 2nd Edition. Routledge: London. Beaver, G. and Hutchings, K. 2005. Training and developing an age diverse workforce in SMEs: The need for a strategic approach. Education + Training, 47(7/8), 592-604. Blanchard, K. 1996. Turning the organizational pyramid upside down, The Leader of the Future. The Drucker Foundation. Editors F. Hesselbein, M. Goldsmith, and R. Beckhard. San Francisco: Jossey-Bass Publishers. pp.81-88. Brokaw, T. 1998. The Greatest Generation. New York: Random House. Carte, T. A., Chidambaram, L. and Becker, A., 2006. Emergent leadership in self-managed virtual teams: A longitudinal study of concentrated and shared leadership behaviours. Group Decision and Negotiation, 15, 323-343. Cisco 2011. Connected World Report. Cisco. Covey, S. C. 1996. Three roles of the leader in the new paradigm. The Leader of the Future. The Drucker Foundation. Editors F. Hesselbein, M. Goldsmith, and R. Beckhard. San Francisco: Jossey-Bass Publishers. pp. 149-160. Crampton, S. M. and Hodge, J. W., 2007. Generations in the workplace: Understanding age diversity. The Business Review, 9(1), 16-22. Demirdijian, Z. S., 2012. The millennial generation’s mindset: Susceptibility to economic crisis. The Business Review, 19(2), 1-11. Drucker, P. F. 1985. Innovation and Entrepreneurship: Practices and Principles. New York:
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- 36. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 34 Nicholson, D. B., Sarker, S., Sarker, S., and Valacich, J. S. 2007. Determinants of effective leadership in ainformation systems development teams: an exploratory study of face-to-face and virtual contexts. Journal of Information Technology Theory and Application, 8(4), 39- 49. Oh, Se-Hyung. 2012. Leadership emergence in autonomous work teams: Who is more willing to lead. Social Behavior and Personality, 40(9), 1451-1464. Orsburn, J. D. & Moran, L. 2000. The New Self-Directed Work Teams: Mastering the Challenge. New York: McGraw Hill. Payment, M. 2008. Millenials: The emerging workforce. Interview with Carol Christen. Career Planning and Adult Development Journal, 34(3), 23-32. Pew Research Center. 2010, February 24. The millennials :confident. connected. open to change. Retrieved November 12, 2010. From http://pewresearcg.org/pubs/1501/ millennials-new-surveyy-generational-personality-upbeat-open-new-ideas-technology- bound. Praveen Parboteeeach, K. and Cullen, J. B. 2012. Strategic International Management. International Edition. New York: SouthWestern CENGAGE Learning. Randeree, K. and Ninan, M., 2011. Leadership and teams in business: a study of IT projects in the United Arab Emerites. Journal of Managing Projects in Business, 4(11), 28-48. Robbins, S. and Judge, T. 2012. Organizational Behavior (15e/Global) Pearson: Prentice Hall Scheck, M., 2012. Training and management of pilots across generations. International Journal of Business and Social Science, 3(3), 137-150. Shirky, C. 2008. Here Comes Everybody. New York: Penguin. Silbergh, D. and Lennon, K., 2006. Developing leadership skills: Online vs. Face-to-face. Journal of European Industrial Journal. 7(30), 498-511. Straus, W, and Howe, N. 1991. Generation: The History of Americas Future. 1584-2069. New York: Quill William Morrow. The Drucker Foundation. 1996. Foreword. P. Drucker. The Leader of the Future. The Drucker Foundation. Editors F. Hesselbein, M. Goldsmith, and R. Beckhard. San Francisco: Jossey-Bass Publishers. pp. xi-xv. Toone, J. E. 2012. Mirage in the Gulf: Examining the upsurge in FDI in the GCC and its legal and economic implications for the MENA region. Emory International Law Review, 26(2), 677-731. Trzesniewski, K. H. and Donnellan, M.B., 2010. Rethinking the “Generation Me” : A study of cohort effects from 1976-2006. Perspectives on Psychological Science, 5, 58-75. Twenge, J. M. 2006. Generation Me: Why Today’s Young Americans Are More Confident, Assertive, Entitled__and More Miserable Than Ever Before. New York, Free Press. U. S. Department of Education. http://www.ed.gov/rschstat/landing.jhtm U.S. Department of Commerce. http://www.commerce.gov/ ; www.census.gov. Ulrich, D. 1996. Credibility X Capability. The Leader of the Future. The Drucker Foundation. Editors F. Hesselbein, M. Goldsmith, and R. Beckhard. San Francisco: Jossey- Bass Publishers. pp. 209-220. Welch, J. and Welch, S. 2007. Winning. New York: Mass Market Paerback. Zigurs, I., 2003. Leadership in virtual teams: Oxymoron or opportunity? Organizational Dynamics, 3(4), 339-351. Zivick, J., 2012. Mapping global virtual team leadership actions to organizational roles. The Business Review, Cambridge, Maryland. 19(2), 18-25. Zopiatis, A., Krambia-Kapardis, M, and Varnavas, A. 2012. Y-ers, X-ers, and Boomers: Investigating the multigenerational [mis]perceptions in the hospitality workplace. Tourism and Hospitality Research, 12(2), 101-121.
- 37. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 35 APPENDIX Survey Please fill out the following survey related to the team you belonged to. Answer all the questions posed honestly. On the Likert scale below, 1 represents no authority, 3 moderate application of authority whereas 5 represents appropriate application of authority). The information you provided on the survey remains confidential. 1. In the team you belonged to, did one of the team members emerge as a leader? Yes----- No----- Who was it?----- 2. Circle whichever personality characteristics the team leader reflected interacting on the team project a. Assertive b. Diligent/Conscientiousness with respect to task completion c. Flexible d. Taking full charge of task completion e. Supportive f. Communicative on different IT media 24/7 g. Dominant 3. How much authority did the team leader exercise when you completed task one of the team project, adding IT features to the blog? 1 3 5 4. How much authority did the team leader exercise when you worked on completing task two of the team project, the collaborative work on the team project? 1 3 5 5. How much authority did the team leader exercise when you and your team mates completed task three, completion of the team project? 1 3 5 6. Based on the leader’s behavior within the team, how much of an entitlement attitude did s/he display. 1 3 5 7. In the space provided below, describe the team leader’s behavior. This paper may be cited as: Akhras, C., 2015. Millennials: Entitled Networking Business Leaders. International Journal of Computer Science and Business Informatics, Vol. 15, No. 1, pp. 23-35.
- 38. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 36 Modeling of Citizen Claims Processing by Means of Queuing System Oleksandr Markovets and Andriy Peleschychyn Social Communications and Information Activity Department, L'viv Polytechnic National University, Ukraine, L'viv, 12 Bandera Str. ABSTRACT This article considers the work of the system “Electronic Reception” as the queuing system. An overview the structure of the system “Electronic Reception” as a chart is given. The initial descriptions for the queuing system are formed. Also scheme simulation model of “Electronic Reception” is represented and found probabilities of states of the system using the application of queuing theory. Context diagram of process of queuing system “Electronic Reception” is designed. Data flow diagrams of the first level of the queuing system “Electronic Reception” and data flow diagram of the subsystem “Analysis of claim” which detailed the context diagram of process of queuing system “Electronic Reception” is designed. A simulation model of single-channel service system “Electronic Reception” is realized. The initial output characteristics of a service system “Electronic Reception” and the parameters of the simulation model are formed. The state probabilities of the service system are found. For a description of the mathematical model queuing system “Electronic Reception” use data that were obtained in one of the experiments. Keywords Queuing system; Simulation model; States marginal probability; Consolidation; Electronic Reception; System. 1. INTRODUCTION Under the modern conditions of information technologies development, increases the role of the Internet in people's lives has emerged the concept of "information society". Therefore there is a necessity to implement electronic governance for communication between authorities and citizens in various spheres of life. One example of such contact is the implementation of electronic public receptions. The main purpose of electronic receptions is providing the citizens with passive and active access to public information, electronic consulting, collecting and analyzing citizens' views about current events, issues. Informational services, provided by electronic reception, include: receiving electronic claims and offering electronic consultation, receiving claims which are addressed directly to the heads of departments of the city council [1].
- 39. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 37 The advantages of implementing electronic receptions in the field of electronic governance are: • ensure transparency of information by public authorities (citizen can track their claims at all stages of consideration); • citizens save time (you can get consultation through the Internet and personal computer at home); • access to resources at any time; • saving privacy of citizens. Despite listed above advantages, still remain some disadvantages: • the processing time is unknown; • because of large number of claims, some can be lost and not considered; • the time it takes to review an claim, may exceed the time limits specified in the notice of consideration of claims and therefore claims may remain unanswered. In this case, in order to assess the performance of electronic receiving and, if necessary, to make it more efficient, it is necessary to analyze it as a queuing system. It is necessary to solve a number of problems that may arise in the queuing system. The main reason of these problems is irregular income of claims. It is not possible to predict how and when complaints will be received by the queuing system "Electronic Reception", and so there can be cases when the system may not cope with incoming applications. There is a negative state of system when system is almost always in a state of inaction. In such case, the cost of its implementation is not justified [2]. It is important to organize the system to increase its throughput and minimize losses of claims. On this depends on the number of channels that are working on stream of claims, their productivity and discipline service. Therefore it is important to analyze the work of the "Electronic Reception" in artificially created conditions to obtain empirical results for the proper relationship of government with citizens and quick respond. 2. THE ACTUALITY OF THE RESEARCH The current planning problem of department activities in processing appeals of citizens is quality determination of the department workload elaboration and possibility to process the appropriate number of electronic appeals by managers. Analytically can be defined only a part of performance indicators of these departments. The basic indicator that characterized work quality of the department is number of electronic appeals that are not elaborated in due time, so-called overdue appeal. In existing system, the pendency time of
- 40. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 38 electronic appeal from the receipt time is impossible to determine by mathematical means. Despite this requirement using simulation modeling is obvious and undeniable. To construct the imitation model it is necessary to reproduce as accurately as possible all the processes that occur in the system. This requires analyzing in detail all system components and the relationships between these components. Established simulation model of system of electronic processing of appeals applied and successfully used in the field of e-governance, particularly in city councils that in improved service delivery to the city citizens are interested. Also, this model is used in the educational organizations in order to establish feedback to applicants, students, teachers, and, in general, institutions, organizations and companies to establish regular contact with its customers and to receive quickly respond to the proposals, complaints or shortcomings in the work. 3. MODELING OF FUNCTIONING PROCESS OF QUEUING SYSTEM "ELECTRONIC RECEPTION" The article is supposed to explore applying queuing systems in claims processing with the aim to consolidate information. Thus, there will be description of processes that occur in the "Electronic Reception", formulation of baseline characteristics of the structure of the queuing system and found marginal probabilities of states based on the results of simulation [3]. To represent the system of electronic reception and further define primary characteristics of the queuing system, it is necessary to build data flow diagram, which will show the major stages of the processing of citizens’ claims in the system. Queuing system "Electronic reception" new claims processed claims Departments of the City Council Users claims reply Figure 1. Context diagram Contextual diagram shows two external entities, which queuing system "Electronic reception" interacts with. The first external entity represents citizens who are users and source of claims in the system. The second external essence denotes structural units (departments of the City Council). They are receiving citizens’ claims coming from email reception, and after processing requests, send a reply back to the email reception. The diagram is further detailized to trace the claim from its ingress in electronic reception to the end of consideration process, in other words, to the moment when the users receive an response email.
- 41. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 39 reply new claims processed claims incoming flow of applications 1.1. Analysis of claim 1.4. Sending a reply 1.3. Processing claims in certain department Information about claims and users data storage data about users and status of claims 1.2. Deleting spam spam change the status of claims confirm the deletion Figure 2. Data flow diagram of the first level of the queuing system "Electronic Reception» Figure 2 shows the major subsystems that a claim passes, namely: • analysis of a claim; • deleting spam; • processing claim in certain departments; • sending a reply. After analyzing the subsystems that resulted from the decomposition of contextual diagrams we can conclude second level decomposition of the subsystems "Analysis of claims" and "Reply to the user." is possible. The first subsystem "Analysis of claims", which is shown in Figure. 3, is divided into the following processes: • analysis of user data and text of claim; • definition of the claim category and appropriate department; • sending a claim to the department; • composing of a response. Input data of subsystem: incoming flow of applications. Output data of subsystems: spam, responses, new claim, entering information into the database.
- 42. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 40 1.1.4. Formulation and responses 1.1.2. Definition of the category claims and department 1.1.1 Analysis of user data and text claims 1.1.3. Sending an claim to the department new claims incoming flow of applications spam data about users and status of claims data storage confirm the deletion Figure 3. Data flow diagram of the subsystem "Analysis of claim" After sending an claim through the City Council portal to the electronic reception, text and user data should be analyzed and identified the nature of the claim: a request, complaint, question, etc. Because electronic reception performs multiple functions, the claims it receives have different types that may give priority to one type of claim over the other claims. Claims that require immediate consideration are processed first. If the electronic reception gets large number of claims, it forms a queue, which can be limited in time during which claim is waiting to be considered. The time allotted for consideration of one claim from the moment of its filing, is defined by the statement of City Council about consideration of electronic applications. At this stage, it is determined whether a claim is not spam. This can be deduced from the text of the claim and user`s personal data. If claim is identified as a spam, it is not considered and it leaves the system. Another important feature that indicates user while filling online electronic forms is a claim category. This feature determines the department to which a claim will be sent for further processing. Also from the contents of claim depends on which service stage it goes: if the claim does not require detailed review and electronic reception employee can consult a user himself, it proceeds to the stage of formation response. If the employee cannot provide answer or fulfill the request contained in the claim he sends this claim to the department assigned for dealing with the particular category of applications. Moreover at this stage employee records in database all information about a claim, user`s personal data and defines the status of claim (e. g. e-considered, under consideration). The start of
- 43. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 41 considering claim and date of its completion is added to the status of a claim. 1.4.1. Preparation posts 1.4.3. Send a reply to email 1.4.2.Fixing discuss treatment completion status in the database processed claims change the status of claims reply Figure 4. Data flow diagram of the subsystem "Sending reply» Subsystem "Send reply" is used to form the response to claim and fix status of claim. This subsystem includes three processes: preparing the message, fixation status, completion of claim in the database and send reply to the user’s e-mail. Input data of subsystem: response to claim, processed claim. Output: responding to claim. At this stage, processed claims are reviewed in the appropriate department, the status of the claim is labeled in the database as "processed" and a reply for the user is prepared. 4. FORMATION OF THE INITIAL OUTPUT CHARACTERISTICS OF A SERVICE SYSTEM "ELECTRONIC RECEPTION" AND THE PARAMETERS OF THE SIMULATION MODEL Baseline data of the service system is determined by the structure and processes taking place in the “Electronic Reception”. In order to comprehensively evaluate the functionality of the service system, are created the critical conditions, using the assumption of the simplest flows. Thus, the system “Electronic Reception” is the service system of type M/M/1, which means that the input is the simplest and the requests service of time is exponentially distributed. As a result, the output stream is also the simplest. The single-channel service system "Electronic Reception" is a system of type with unlimited standby on which the input flow comes, which may take
- 44. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 42 in the citizens` claims of three types: application of the relative priority (claim1), application of conventional type (claim2) and processed claim that only requires an answer (claim3). An arrival time of application is determined by the exponential distribution law. The service time is given to implement the system with priority, but it is believed to be exponentially distributed [4]. Only one claim is served by a channel at a time period. If the channel is not loaded when a message comes, claim will be processed. If there are no claims, the system is idle. The discipline of service is following: if the system is already analyzing an ordinary claim or a processed claim, the claim with priority does not displace the claim of these types of services, and becomes the next. If the system has no claim with priority, claims are served according to the FIFO discipline. If the system has several claims with priority, they are ordered for processing adhering to the rules of the discipline FIFO discipline. Basing on the described above initial output characteristics perform, the simulation model is constructed and common parameters to the system as a whole and blocks separately are formed. As a result of simulation and analysis of the results is proved that the number of service channels, necessary for the simplest flows manages flows and other types processing. FIFO path combiner (setting priorities) Exponentially distribution Exponentially distribution Exponentially distribution answeranswer Claim 1Claim 1 Claim 2Claim 2 Claim 3Claim 3 uniform distribution Figure 5. A simulation model of single-channel service system "Electronic receiver» 5. FINDING STATE PROBABILITIES OF THE SERVICE SYSTEM This chapter is based on data obtained through simulation, we use the formulas of the applications of the theory of service system to describe the
- 45. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 43 mathematical model QS "Electronic receiver" type M/M/1 and M/M/2, and thus find the probability states in which the system may be. For a description of the mathematical model QS "Electronic receiver" type M/M/1 use data that were obtained in one of the experiments. It is necessary to describe all possible states of single-channel service system "Electronic Reception": • 0S – service channel is free; • 1S – service channel is busy, but there are no queues; • 2S – service channel is busy, there is a claim in the queue; • mS – service channel is busy, all m claims are queuing, the condition λ<μ should be true. Calculate the value of μ:. 897666,0 114,1 11 sert . From the formula we find λ: 351436,0897666,03915,0 . Since the intensity of the input stream λ is smaller than the intensity of the channel and the load factor μ ρ <1, the marginal probability of the system exists and the queue is not growing constantly. As a result of the service system "Electronic Reception" will go down in a steady (stationary) mode. The relative bandwidth of the system is 1 serPQ , and the absolute bandwidth is. To find the probability of system states we use already defined formulas that describe the processes of "death and reproduction." The probability that the message will be processed proP is 1, and in turn, the probability of denial of service denP is 0. The maximum probability that channel of maintenance is free, determined by the ratio 6085,03915,0110 p , it means that 60.85% of the system is in a free state. The probability that the servicing channel is busy: 3915,06085,011 0 busyp , it means 39.15% system busy. Maximum probability that the servicing channel is busy, but there is no queue, is 2382,0238228,06085,03915,0)1(1 p which means, that the probability of such an event is 23.82%.
- 46. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 44 Maximum probability that provided employment service facility, in turn is one appeal, is 0933,0093266,06085,03915,0)1( 22 2 p , that the probability of this event is 9.33%. Maximum probability that provided employment service facility, in turn is two appeals, is 0365,0036514,06085,03915,0)1( 33 3 p , that the probability of this event is 3.65%. The probability that the queue waiting to be of service to two appeals is 368,0368008,0)3( 321 pppkP . Thus, considering the counted above probability of the system states, could be made the following statement: the single-channel service system will be in the free state, which increases the probability of received claims to be sent for considering. For multi-channel service system of type M/M/2 characterized by the following conditions: • 0S – all channels are available, k = 0; • 1S – one channel is busy, other free, k = 1;; • nS – busy all 2 channels, no queues, k = 2; • 1nS – both channels are busy, one requirement in line k = 3; • rnS – all n channels are busy, r requirements in line, k = n + r Calculate the value of μ and λ: 97276265,0 028,1 11 sert ; 53715954,097276265,05522,0 Relative and absolute bandwidth equal, respectively, Q = Рser = 1 and 53715954,0 QA . The probability that the message will be processed is 1, and the probability of failure is 0. Maximum probability that service channels are at rest is 567,0 4478,12 5522,0 2 5522,0 1 5522,0 1 )2(!2!2!1 1 132132 0 p The probability that one, two or three appeals are processed is: 3131,03130974,0 !1 01 pp or 31,31%;
- 47. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 45 0865,008644619,0 !2 0 2 2 pp or 8,65%; 0159,001591186,0 !3 0 3 3 pp or 1,59%. The probability that in the queue are one or two appeals is defined as follows: 0239,002386779,0567,0 22 5522,0 !22 3 01 3 12 pp ; 0066,0006589897,0567,0 24 5522,0 !22 4 02 4 22 pp The probability that the queue will be formed is: 0329,00329711198,0 )2(!2 0 3 q pP . The average number of available channels is 4478,15522,02a nn , and the employment rate channel is 2761,0 2 5522,0e e nn n k . Thus, multi-channel service system is the equal time period in free and busy state, which may indicate that the system is functioning normally. 6. CONCLUSIONS In the article the structure of the "Electronic Reception" is suggested and the initial baseline of characteristics for the service system is formulated. The simulation model of the queuing system "Electronic Reception" is presented and the probability of boundary conditions of the system is determined. Efficiently performed modeling of functioning process of queuing system "Electronic Reception" is allow creating a system that can provide an opportunity to give electronic consultations to citizens on various issues timely. As a result, the implementation of electronic receptions in the field of electronic governance ensure transparency of information by public authorities, save time of citizens, give access to resources at any time and save privacy of citizens. Also, the result of modeling implementation allows effectively plan electronic reception functioning, to analyze the possible problems that arise in the system, to calculate the required material, financial and human resources.
- 48. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 46 7. REFERENCES [1] Serenok, A., 2011. Introduction of technologies of e-government in activity of organs of local self-government, Journal of Kharkiv Regional Institute of Public Administration of the National Academy of Public Administration, No. 1. [2] Markovets, O., Peleshchyshyn, A., Zhezhnych, P., 2011. Designing a system processing appeals to local authorities, Computer Science and Information Technology: Proceedings of the National University "Lviv Polytechnic", No.694, pp. 153-160. [3] Markovets, O., 2011. A mathematical model for the applicant of e-government, Information Systems and Networks: Proceedings of the National University "Lviv Polytechnic", No. 699, pp.154-163. [4] Anikovskiy, V., Erofeeva, L., Novgorod, N., 2010. Elements of queuing theory. Basic concepts. Tasks. Guide to solving problems, Novosibirsk State Technical University. This paper may be cited as: Markovets O. and Peleschychyn A., 2015. Modeling of Citizen Claims Processing by Means of Queuing System. International Journal of Computer Science and Business Informatics, Vol. 15, No. 1, pp. 36-46.
- 49. International Journal ofComputer Science and Business Informatics IJCSBI.ORG Suggestions for Informational Influence on a Virtual Community R. V. Huminskyi Hetman Petro Sahaidachnyi Army Academy, Lviv, Ukraine A. M. Peleshchyshyn Lviv Polytechnic National University, Lviv, Ukraine Z. Holub Lviv Polytechnic National University, Lviv, Ukraine ABSTRACT The growing popularity of social networks made them a perfect platform for informational warfare. They are widely utilized in influencing miscellaneous processes of human interaction, namely opinion formation, decision making, imposing goals and spreading information. Such interference in people’s behavior poses a threat to the personality and the society as a whole. An open problem is to reduce the informational hazard in virtual communities to the threshold value. Our contribution to the solution of the problem is the algorithm of choosing discussions of a virtual community that are suitable for the influence on the internal informational space. The algorithm in action is demonstrated on the virtual community model. In this paper we dwell on one stage of the algorithm, particularly making suggestions. On this stage, the list of discussions unsuitable for informational influence (prohibited discussions) is composed. The experiments results have proved the significance of this stage and the advantages of influencing a virtual community with the list of prohibited discussions in getting accurate outcome. Keywords Informational influence, Informational hazard index, Prohibited discussion, Virtual community, Group value, Information space, Reachability matrix. 1. INTRODUCTION The Social networks development and increase in the number of users, which ensued from continuous improvement of the tools, made social networks an ideal base for creating virtual communities. Owing to the content diversity of virtual communities` discussions, the users have an opportunity to join a related to their fields of interest conversations. As a result discussions could be used for conducting social researches, finding out people`s attitudes to various fields of consideration (politics, culture, etc.). Besides, as time goes by they are more and more used in information wars, namely electoral competitions, marketing products or services in the competitive space, or affecting collective conscience. The last could be carried out with the aim to change people`s behavior, impose ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 47
- 50. International Journal ofComputer Science and Business Informatics IJCSBI.ORG goals, that either don`t correspond to their interests or contain information risks to an individual, society or state. Thus, there exist not only beneficial to society virtual communities aiming at enhancing society`s well-being as a whole, or separate social groups and individuals life, however social networks are more and more used for creating destructive virtual communities. Destructive communities do not exclude illegal methods from their strategies. They direct their aggression at opposing social networks or generally at society. One of the methods used in information wars and preventing information hazards is informational influence, which is employed for informational management. In this case informational management means providing the objects of influence with the information that will make them alter the course of their behavior. Informational influence success to the great extent depends on the right choice of the object for informational influence. To put it differently information advantage is essential. This necessity is a result of the complicated discussion structure of virtual communities. Due to the immense network of interconnected with hyperlinks discussions and numerous registered users, the informational influence on all virtual community`s constituents at once is impossible. 2. RELATED WORKS The rules, following which a state could combat informational influence of virtual communities, are presented in [1, 2]. They are: • Applying force - shutting down servers; • Legal – prosecuting virtual community members; • Monitoring and exercising of informational influence methods with the aim to fight the informational influence of virtual communities. Monitoring and exercise of informational influence methods to fight virtual informational influence of communities is proved to be in the long run the most efficient of three enlisted previously methods. These methods give opportunity not only to cease or slow down virtual communities activities but change their ideology. In the research [3] the model of virtual community informational space, which consist of exterior and internal informational space, was created. Taking into account the model of informational space presented in [4, 5] was worked out informational hazard index. It is utilized to measure the informational hazard level. The following constituents of informational space are considered: ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 48
- 51. International Journal ofComputer Science and Business Informatics IJCSBI.ORG • The number of virtual community members; • The amount of operating assets; • The amount of virtual community content; • Discussion relations structure of a virtual community. In order to resist and fight informational hazards in virtual communities it was researched how to choose the appropriate strategy of informational influence on internal virtual community space. The strategies of influence on the internal space of the virtual community were worked out according to the rules of counteraction to informational hazards in virtual communities. Strategy 1. Discussions banning, that means decrease in discussions and members number. Strategy 2. Destroying discussions` relations, doesn`t involve without diminishing discussions and members number. Strategy 3. Destroying discussions` relations, with the aim of forming groups of discussions, doesn`t involve without diminishing discussions and members number. Conducted researches [6] showed that the most efficient in influencing the structure of virtual community`s informational space are mixed strategies. Before making this deduction the following influence types were studied: • Discussions’ relations destroying by means of discussions banning; • Informational influence on discussion content in order to reduce the degree of messages relevance to the discussion`s topic, which would result in transferring the discussion to rival virtual community. 3. STATING THE PROBLEM In this paper the following model of internal informational space [3] is employed: )itytualCommunShadow(Vir)itytualCommunMember(Vir al(Tread),LinkIntern),itytualCommunThread(VirmunityVirtualComInfSpace ii ii , )( = where )itytualCommunThread(Vir i means the totality of the і-th virtual community discussions; where )itytualCommunThread(Vir i means the totality of the і-th virtual community discussions; )(ThreadalLinkIntern means discussions relations matrix of the і-th virtual community; ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 49
- 52. International Journal ofComputer Science and Business Informatics IJCSBI.ORG )itytualCommunMember(Vir i means the set of registered in social networks і-th virtual community participants (members); iN j ji ThreadMember)itytualCommunMember(Vir 1 )( = = , where )( jThreadMember represents the set of registered in social networks j-th discussion participants; iN represents the number of і-th virtual community discussions; )itytualCommunShadow(Vir i represents the set of registered in social networks users interested in the discussed in the i-th virtual topics; iN j ji )eadShadow(Thr)itytualCommunShadow(Vir 1= = , where )eadShadow(Thr j stands for the set of registered in social networks users, who despite being interested in a discussion do not participate in it; iN stands for the number of і-th virtual community discussions. Provided: )itytualCommunShadow(Vir)itytualCommunMember(Vir ii ≠ . A virtual community is presented by means of matrix method [7, 8] as a disconnected, undirected graph. ),( AVG = where V denotes the set of vertices that represents the totality of the i-th virtual community discussions )itytualCommunThread(Vir i ; A denotes the graph`s G adjacency matrix that represents the elements of virtual community discussions relations matrix; )(ThreadalLinkInternA = According to [3] the matrix of relations between the discussions of the i-th virtual community has the following look: ,)( *nnijlinkThreadalLinkIntern = where ijlink indicates the existence of hyperlinks between the i-th and the j- th discussions of the virtual community; n denotes the number of discussions in the virtual community; ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 50
- 53. International Journal ofComputer Science and Business Informatics IJCSBI.ORG The presence of a hyperlink between the i-th and the j-th discussions in the virtual community is determined in the following way: Or: where iersThreadMemb denotes the set of the i-th discussions members. Vertices weights could be calculated on the grounds of discussions` characteristics )( iThreadSim and the following discussion model [3]: )(),(,,, iiiiii ThreadLinkThreadPostersThreadMembriptionThreadDesceThreadTitlThread = where ieThreadTitl represents the i-th discussion title; iriptionThreadDesc represents the i-th discussion description; iersThreadMemb represents the set of the the i-th discussion members; { } )( 1 )( iPT N jiji PostThreadPost = = represents the set of the messages, that constitute the i-th discussion; )( iPT N represents the number of messages in the the i-th discussion; )( iThreadLink represents the set of hyperlinks, that are in the i-th discussion informational content. Thus vertices weights are denoted as niii ersThreadMembcardThreadSimV ,1 )(),( = = where )( iThreadSim stands for the degree of relevance of the i-th discussion posts to its topic; )( iersThreadMembcard stands for the number of discussion members. Thus, the aim is, by means of the graph theory algorithm, to solve the problem of finding the shortest list of the virtual community discussions, which deletion would reduce the information hazard index of the virtual community to the threshold level. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 51
- 54. International Journal ofComputer Science and Business Informatics IJCSBI.ORG 4. THE ALGORITHM OF CHOOSING DISCUSSIONS The algorithm outcome is the minimal amount of the virtual community discussions sufficient for performing informational influence on the internal space aiming at reducing informational hazard to the threshold level. Running the algorithm the following complementary goals are reached: • Discussions groups forming; • When applying the algorithm repeatedly, the feedback of informational influence on the virtual community should be taken into account. The overall algorithm is depicted on Figure 1. Assessing value of every discussion group END Forming groups of discussions )( iGroupValue Finding the group with the highest value max)( →iGroupValue Choosing a discussion for II Excluding the discussion from VC Calculating information hazard index )( munityVirtualComInfTreat * )( InfTreat munityVirtualComInfTreat > Making suggestions BEGIN Так Ні Block 1 Block 2 Block 3 Block 4 Figure.1: The flow chart of the algorithm of choosing virtual community discussions suitable for the influence on the internal informational space. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 52
- 55. International Journal ofComputer Science and Business Informatics IJCSBI.ORG 4.1 Block 1 Discussion groups have to be formed according to the following rules [4,5]: • The group can`t be empty, it should consist at least of one discussion. • A virtual community can contain from 1 to n groups (n means a number of discussions in a virtual community), therefore the group can contain from 1 to n discussions. • All discussions are interconnected with internal and exterior hyperlinks or have common members. Discussions, not connected with any discussion of the group, found another group. • All discussions of the group have no internal or external hyperlinks and no common members with the discussion from the other groups. Otherwise, the groups have to be referred as to one. Next step is to assess the value of the formed groups. The formula for calculating virtual community group value is presented further: ( ) ( ) ( )∑ ∑ ∑ = = = ⋅− − ⋅⋅ ⋅⋅= )( )( )( 1 1 1 )()( )()(ln )()()( iGroup iGroup iGroup M j jj M j jj M j jji ersThreadMembcardThreadSim ersThreadMembcardThreadSim ersThreadMembcardThreadSimGroupValue where jersThreadMemb represents the set of the j-th discussion participants; )( jThreadSim stands for the degree of the j-th discussion`s topic relevance; )( iGroup M stands for the number of discussions in the j-th group. The degree of relevance is calculated by the equations described below [3]: ( )( ) ( )( )∑ ∑ = = + − = )( )( 1 )()( 1 )( iThread i iThread N j i flood j Thread N j ij i ThreadPostcardN ThreadPostcard ThreadSim where )( ij ThreadPost+ the set of the і-th discussion’s positive messages; ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 53
- 56. International Journal ofComputer Science and Business Informatics IJCSBI.ORG )()( i flood j ThreadPost means the set of the i-th discussions messages that in light of the virtual community subject matter convey no useful information; )( iThread N means the number of the і-th discussions messages. And ( ) ( )∑ ∑ = = + = )( )( 1 1 )( )( )( iThread iThread N j ij N j ij i ThreadPostWeight ThreadPostWeight ThreadSim where ( ))( ij ThreadPostWeight + denotes the weight of the і-th discussion`s positive messages; )( iThread N denotes the number of the і-th discussions messages. ( ) )( * )( * )( )( i ijiThreadCentroid i ThreadCentroid Postw ThreadCentroid ij M w ThreadPostWeight ∑ ∈ = , wherе * )( iThreadCentroidw represents the weight of the keyword from the і-th discussion centroid, which is in the j-th post of the i-th discussion; )( iThreadCentroidM represents the number of the keywords from the і-th discussion centroid, which are in the j-th post of the i-th discussion; The group that has the highest value of all other groups and contains more than two elements is to be selected. 4.2 Block 2 Before applying informational influence, it is necessary to decide on a discussion or several suitable for informational influence discussions. Further step is excluding the discussion from the virtual community, this can be achieved either by applying power (shutting down a discussion) or by informational influence (reducing the degree of the discussion topic relevance and discussion transfer to the rival virtual community). 4.3 Block 3 Calculating the information hazard index for the virtual community that has undergone enlisted above changes [4,5]: ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 54
- 57. International Journal ofComputer Science and Business Informatics IJCSBI.ORG > = 1 )( )( ,1 , )( )( )( * * munityVirtualComValue munityVirtualComValue якщо munityVirtualComValue munityVirtualComValue munityVirtualComInfTreat where )( munityVirtualComValue means virtual community value; * )( munityVirtualComValue means the extreme virtual community value, when the information hazard realises. The content quality and links structure of the virtual community are disregarded. Virtual community value: ( ) ( ) ( ) ⋅− − ⋅⋅ ⋅ ⋅= ∑ ∑ ∑ ∑ = = = = )( )( )( 1 1 1 1 )()( )()(ln )()()( jGroup jGroup iGroup M j jj M j jj N i M j jj ersThreadMembcardThreadSim ersThreadMembcardThreadSim ersThreadMembcardThreadSimmunityVirtualComValue where N – the number of groups in the virtual community; )( iGroup M represents the number of discussions in the і-th group. Extreme virtual community value: ( ) )( )(ln)()( * i ii InfTreatMembers InfTreatMembersInfTreatMembersmunityVirtualComValue − −⋅= wherе )( iInfTreatMembers denotes determined by experts extreme number of a virtual community members, when the information hazard realises. The content quality and links structure of the virtual community are disregarded. If the information hazard index excesses the threshold level go to Block 1. 4.4 Block 4 At this stage suggestions about the list of suitable for information influence on the internal information space discussions are made and expected structure of the internal informational space of the virtual community is composed. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 55
- 58. International Journal ofComputer Science and Business Informatics IJCSBI.ORG 5. DISCUSSION GROUPS FORMING Due to the fact that the virtual community is presented by means of the matrix method, the algorithm of the graph partition into as dense as possible graphs is used. To perform this, the adjacency matrix A is exploited. All the diagonal elements of the adjacency matrix A are equal 1, as long as, each vertex is reachable for itself. Following the parallel algorithm of constructing reachability matrix on the basis of the graph [9], build the reachability matrix R. The constructing reachability matrix algorithm consists of the following steps: 1. Create a reachability matrix . 2. Using the general formula, create a reachability matrix for the k subsequent iterations. 3. Repeat the step 2 until the condition is satisfied: The matrix where the entry of 1 in row i, column j indicates a path from i to j with just one edge 1=ijr , is the result of parallel algorithm of constructing reachability matrix. Having grouped the matrix R by shifting the columns and rows that have similar ordinal numbers, you will build a block diagonal matrix , where the each group of elements denotes a group of virtual community discussions. If all matrix elements equals 1, a virtual community is represented only by one group. If from all elements representing a vertex, only a diagonal element equals 1, the discussion is isolated. 6. DETERMINING THE SUITABLE DISCUSSION Matrix product of n copies of adjacency matrix properties [7, 8] are employed to choose a discussion. Only the existence of the trace between the vertices is of interest, therefore in the matrix exponentiation algorithm arithmetic operations are substituted with logical operations (Addition with disjunction and Multiplication with conjunction). ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 56
- 59. International Journal ofComputer Science and Business Informatics IJCSBI.ORG The algorithm consists of the following steps: 1. Create a reachability matrix . 2. Using the general formula, create a reachability matrix for the k subsequent iterations. 3. Repeat the step 2 until the sum of all row elements of the matrix equals the number of discussions in the group. The outcome of the algorithm are one or several discussions that have the shortest route to all the other discussion groups of a virtual communities. 7. CHOOSING THE DISCUSSION FOR INFORMATIONAL INFLUENCE When choosing a discussion, the list of unsuitable for informational influence discussions (prohibited discussions) has to be considered. The list is a result of revised monitoring and influence strategy decision process. Using the prohibited discussions in carrying out informational influence is impossible because: • The discussion is strongly moderated (administrators and moderators constantly delete undesirable content); • Informational influence had negative results. Therefore, prohibited discussions must be excluded from the list of determined for the informational influence discussions. After that following rules are to be adhered to: • If the discussion list is empty, run the algorithm for k+1 iteration to obtain additional discussions list. • If the list contains only one, choose it for an informational influence object. • If several discussions are available, choose the discussion, which deletion leads to the most dramatic informational hazard rate reduction. If the previous filtering gave more than one results, choose the discussion with the most undefined subject matter. 8. MAKING RECOMMENDATIONS FOR INFLUENCE ON INTERNAL INFORMATION SPACE Recommendations are made after the completion of the full list of discussions, which when deleted, would cause information hazard rate fall to its threshold level. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 57
- 60. International Journal ofComputer Science and Business Informatics IJCSBI.ORG Besides a discussion list, the prospective structure of the internal and external information space of the virtual community after informational influence is sketched. For the further virtual community monitoring is determined the observation window. It gives opportunity to see the results of the informational influence. During the revised social network monitoring are taken all measures to form the virtual community with the determined subject matter. The list of prohibited discussions is made before the revised monitoring. 9. EXPERIMENTAL PART The calculations were made for the virtual community model with the following features showed in Table 1. Table 1. Characteristic features of the virtual community’s models graph № Graph metrics Meaning 1. Vertices (discussions) 500 2. Edges 737 3. Connected components 1 4. Maximal number of the vertices in the connected component 500 5. Maximal diameter of the graph 500 6. Average diameter of the graph 12 7. Graph`s density 5,72 Presented characteristic features of graph of the virtual community model correspond to the previous investigations of social networks structure [10, 11]. Additional features of the community`s discussions are presented in Table 2. Table 2. Characteristics of the virtual community`s discussions № Discussions` characteristics Meaning 1. Minimal number of members 100 2. Maximal number of members 1000 3. The lowest degree of posts relevance to the topic of the discussion 0,5 ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 58
- 61. International Journal ofComputer Science and Business Informatics IJCSBI.ORG 4. The highest degree of posts relevance to the topic of the discussion 1 Calculations were carried out for the two virtual community types: Type 1. Virtual communities with no list of prohibited discussions, which usage in carrying out informational influence is impossible. Type 2. Virtual communities with provided list of prohibited discussions, which usage in carrying out informational influence is impossible. The list is composed on the basis of calculations made for the Type 1. For both types calculations are repeated until information hazard index drops to its threshold value – 0,5. Graphs structures for type 1 and type 2 are depicted in the figures 1 and 2 correspondently. denotes objects (discussions) determined for informational influence (Type 1) Figure 2. Virtual community structure (Type 1) ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 59
- 62. International Journal ofComputer Science and Business Informatics IJCSBI.ORG objects (discussions), determined for informational influence (Type 1) prohibited discussions, that can`t be subjected to informational influence Figure 3. Virtual community structure (Type 1) Calculations results for the type 1 and type 2 are presented in the Table 1 and 2 correspondingly. Table 3. Calculations results for the Type 1 Step ObjectoftheII Groupscount Isolateddiscussionscount Informationalhazard indexoftheVC Reduction of an informational hazard index: Total Bymeansof destroyingVC structure Bymeansof excludingVC elements 0 1 0,723 1 5 1 2 0,721 0,002 0,002 0,000 2 128 2 9 0,670 0,052 0,051 0,001 3 1 3 13 0,642 0,081 0,079 0,002 4 224 3 20 0,634 0,088 0,086 0,002 5 311 3 20 0,633 0,089 0,087 0,002 6 428 4 32 0,621 0,102 0,099 0,003 7 101 4 38 0,615 0,108 0,105 0,003 8 196 4 42 0,610 0,112 0,109 0,004 9 435 4 53 0,599 0,123 0,118 0,005 10 201 4 57 0,595 0,128 0,122 0,005 11 253 4 59 0,593 0,129 0,124 0,006 12 135 4 70 0,583 0,140 0,133 0,007 13 401 4 75 0,579 0,143 0,136 0,007 14 470 4 79 0,573 0,150 0,141 0,008 15 132 4 85 0,565 0,158 0,148 0,010 ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 60
- 63. International Journal ofComputer Science and Business Informatics IJCSBI.ORG 16 496 4 89 0,560 0,163 0,153 0,010 17 487 4 90 0,558 0,165 0,154 0,011 18 265 4 96 0,552 0,170 0,159 0,011 19 336 4 96 0,551 0,172 0,160 0,012 20 345 4 99 0,547 0,176 0,164 0,012 21 459 5 102 0,536 0,187 0,174 0,013 22 293 5 105 0,532 0,190 0,177 0,013 23 300 5 106 0,528 0,194 0,181 0,013 24 165 5 107 0,527 0,196 0,182 0,014 25 209 5 115 0,521 0,202 0,188 0,014 26 129 5 122 0,512 0,211 0,195 0,016 27 429 5 127 0,508 0,215 0,198 0,016 28 121 5 129 0,505 0,218 0,200 0,017 29 398 5 136 0,498 0,224 0,206 0,018 Table 4. Calculations results for the Type 2 Step ObjectoftheII Groupscount Isolateddiscussionscount Informationalhazard indexoftheVC Reduction of an informational hazard index: Total bymeansof destroyingVC structure bymeansof excludingVC elements 0 1 0,723 1 5 1 2 0,721 0,002 0,002 0,000 2 230 1 7 0,714 0,008 0,007 0,001 3 278 1 11 0,708 0,016 0,014 0,002 4 218 1 12 0,707 0,028 0,014 0,002 5 152 1 12 0,695 0,026 0,014 0,004 6 187 1 12 0,696 0,026 0,014 0,005 7 204 1 12 0,697 0,025 0,014 0,006 8 227 1 12 0,698 0,025 0,014 0,006 9 224 2 18 0,689 0,034 0,023 0,011 10 209 2 25 0,682 0,040 0,029 0,011 11 144 2 28 0,678 0,044 0,032 0,012 12 253 2 30 0,677 0,046 0,034 0,012 13 300 2 32 0,672 0,050 0,037 0,013 14 165 2 34 0,670 0,053 0,039 0,014 15 270 2 35 0,668 0,055 0,041 0,014 16 176 2 35 0,668 0,055 0,041 0,014 17 170 2 39 0,664 0,059 0,045 0,014 18 181 2 41 0,660 0,063 0,048 0,015 19 214 3 41 0,618 0,105 0,089 0,016 20 196 3 45 0,613 0,110 0,093 0,017 21 246 3 47 0,611 0,111 0,094 0,017 22 139 4 48 0,605 0,117 0,099 0,018 23 293 4 48 0,602 0,120 0,102 0,019 ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 61
- 64. International Journal ofComputer Science and Business Informatics IJCSBI.ORG 24 173 4 51 0,600 0,122 0,103 0,019 25 265 4 58 0,594 0,128 0,109 0,019 26 435 4 68 0,576 0,147 0,126 0,021 27 249 5 70 0,571 0,152 0,131 0,021 28 110 6 70 0,553 0,170 0,148 0,022 29 401 6 75 0,550 0,173 0,151 0,022 30 496 6 80 0,544 0,178 0,156 0,023 31 470 6 83 0,538 0,185 0,162 0,023 32 487 6 84 0,534 0,189 0,166 0,023 33 336 6 84 0,534 0,188 0,164 0,024 34 345 6 87 0,530 0,192 0,168 0,024 35 459 7 90 0,519 0,204 0,179 0,025 36 82 8 95 0,510 0,212 0,187 0,025 37 429 8 101 0,507 0,216 0,190 0,026 38 311 8 102 0,506 0,217 0,191 0,026 39 428 8 114 0,494 0,228 0,202 0,026 Figure 4 presents changes of the information hazard index value for the Type 1and Type 2. Figure 4. Changes of the information hazard index value for the Type 1and Type 2 Foreseen post-influence structures for the Type 1 and Type 2 virtual communities are presented in the Figures 4, 5 correspondingly. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 62
- 65. International Journal ofComputer Science and Business Informatics IJCSBI.ORG Figure 5. Foreseen post-influence structures for the Type 1 virtual community Figure 6. Foreseen post-influence structures for the Type 2 virtual community The maximal information hazard reduction is reached when mixed informational influence strategies are applied in the process of groups forming (steps 2, 3, 6, 21 for the Type 1 and steps 19, 28, 35 for the Type 2) as well as due to the isolating of a large amount of discussions (steps 9, 12 for the Type 1 and steps 26, 39 for the Type 2). The experiments results showed that reduction of the informational hazard level is achieved not by means of decreasing the quantity of discussions in the virtual community, but owing to destroying virtual community structure. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 63
- 66. International Journal ofComputer Science and Business Informatics IJCSBI.ORG 10. CONCLUSIONS The set in the beginning of the research goals were reached. In other words the problem was formulated and applying graph-theoretic methods was developed an algorithm of making the minimal list of virtual community discussions suitable for the informational influence aiming at informational hazard reduction to its threshold. By repeated algorithm application, the feedback of informational influence on the internal space structure of a virtual community is taken into account. Moreover the list of unsuitable for informational influence discussions (prohibited discussions) is formed. The list contains strongly moderated discussions (administrators and moderators constantly delete undesirable content) and discussions, informational influence on which caused negative results on the participants of the discussion. Experiments results proved that the highest informational hazard index reduction ensued from destroying the structure of internal informational space. Causing a decrease in virtual community discussions count (members of virtual community count) appeared to be less efficient. The maximal informational hazard reduction occur, either by forming separate groups of discussions according to the Strategy 3 or by forming large quantity of isolated discussions corresponding to Strategy 2. 11. REFERENCES [1] Huminskyi, R.V., 2012. Virtual communities as a subject of informational security of the state. Scientific and Practical Journal of Informational Security, 3(56), pp. 18-25. [2] Peleshchyshyn, A.M., 2013. Threats to informational security of a state. Scientific and Technical Journal of Ukraine Air Force, 2(11), pp. 192 - 199. [3] Peleshchyshyn, A.M. and Huminskyi, R.V., 2014. The model of informational space of the virtual community. Eastern-European Journal of Enterprise Technologies, 2/2(68), pp. 10-16. [4] Peleshchyshyn, A.M. and Huminskyi, R.V. Evaluation of informational hazards in the process of virtual communities functioning. In: National Aviation University, 4th International academic conference ITSEC. Kyiiv, Ukraine. 21-24 May 2014. Kyiiv: National Aviation University, pp. 59 – 60. [5] Huminskyi, R.V. and Peleshchyshyn, A.M., 2014. An assessment of informational threat in the functioning process of virtual community. [online] Cybernetic Letters. Available at: <http://www.cybletter.com> [Accessed 05 August 2014]. [6] Peleshchyshyn, A.M. and Huminskyi, R.V., 2014. The selection of the strategy of the informational influence on informational space of the virtual community. In: Lviv Polytechnic National University, 3rd International Academic Conference on Information, Communication, Society. Lviv, Ukraine. 19-21 May 2014. Lviv: Lviv Polytechnic Publishing House, pp.30 – 31. [7] Berge, C., 1958. The theory of graphs and its application. Translated by A.A. Zykova., 1962. Moscow: Foreign Literature Publishing House. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 64
- 67. International Journal ofComputer Science and Business Informatics IJCSBI.ORG [8] Zykov, A.A, 1987. The fundamentals of the graph theory. Moscow: Chief editorial office of physics and mathematics literature. [9] Kniazkova, A.V. and Volchenskaia, T.V., 2014. The parallel algorithm of finding reachability in a graph. [online] Fundamental Researches. Available at: <http:// www.rae.ru/fs/?section=content&op=show_article&article_id=10003049> [Accessed 05 June 2014]. [10]Abramov, K.G., Monachov, Ju.B. and Bodrov, I.Ju., 2011. To the question of social networks topology modeling. In: SFedU (Southern Federal University), 5th All- Russian scientific-practical conference on theory and practice of imitational modeling. Saint Petersburg, Russia. 19-21 Oktober 2011. Saint Petersburg: Southern Federal University, pp. 11 – 14. [11]Hubanov, D.A. and Chkhartishvili, A.H., 2014. Formal and informal connections of users of Facebook social network. In: IMP RAS (The Institute of Management Problems of the Russian Academy of Sciences), 12th All-Russian conference on management issues. Moscow, Russia.16-19 June 2011. Moscow: The Institute of Management Problems, pp. 301 – 309. This paper may be cited as: Huminskyi R.V., Peleshchyshyn A.M. and Holub Z., 2015. Suggestions for Informational Influence on a Virtual Community. International Journal of Computer Science and Business Informatics, Vol. 15, No. 1, pp. 47-65. ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 65
- 68. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 66 VoIP Security: Improving Quality of Service through the Analysis of Secured Transmission Uchenna P. Daniel Ani Federal University Lokoja, Nigeria. Mohammed Mustapha INEC, Abuja-Nigeria ABSTRACT VoIP as a packet switched system is clearly one of the most important evolving trends in computing and telecommunications. However, just like many other new Information technology trends, VoIP introduces both security risks and opportunities for the IT world, viable solutions of which are required. The use of publically verified cryptographic algorithms to ensure confidentiality of VoIP traffic transmitted over insecure public networks as the Internet cannot be overemphasized. Nonetheless, the uses of cryptographic algorithms yet imposes a delay overhead and packet size overhead on VoIP, which is unconnected to the processing time required to encrypt/decrypt bits or blocks of data and the increase in packet size due the block size of the encryption algorithm. This delay levied is dependent on the mode of operation of the cryptographic algorithms. Mindful of the fact that other components like voice codecs and network bandwidth also contributed delay capabilities on VoIP traffic, and additions of security overheads, there exists a threshold point where an increase in call volume exerts a negative effect on pre-established calls with respect to time and the rate of packet loss. This study sought to determine the combination of cryptographic algorithms, cipher mode and voice codec that holds the uppermost threshold point, before the latency and rate of packet loss of active calls goes past ITU acceptable standards; for one way latency in both plain and encrypted VoIP traffic of 150ms and 200ms respectively and 5% packet loss rate. Through simulation of appropriate scenarios, results indicates that each of the encryption algorithms (AES, DES and 3DES) append additional overhead on the e2e delay and rate of packet loss during VoIP transmission. Also revealing that VoIP-supported codecs are faster and have a higher threshold in terms of the number of calls before the e2e delay and the rate of packet loss exceeds the acceptable limit for encrypted and plain VoIP e2e delay and packet loss rate. Keywords VoIP QoS, VoIP Security, VoIP Encryption, Block Cipher Encryption, Stream Cipher Encryption. 1. INTRODUCTION The use of stream media applications such as Voice over Internet Protocol (VOIP) is of great importance in today’s co-operate business strategy, public and private use because it provides a cheap alternative to the
- 69. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 67 traditional telephoning system for both VoIP service provides in terms of infrastructure cost and user calling cost. A 2010 study by IBISWorld showed that VoIP services have the best growth within the Information Technology industry from 2000 to 2009 with a growth of 179,036% [1]. VoIP is a technology that provides circuit switch like telephone service over an IP based network [2], its involves transmitting voice or media data over the internet by converting analogue signal into digital signals by the means of codec and uses Real-time Transport Protocols as the transport media [3]. Because of the increase in acceptance of VoIP technology, there is a need to secure VoIP traffic as the media networking protocol used in transmitting VoIP packet Real-time Transport Protocols has no security feature [4]. However, the increase in both packet size and processing (Encryption/Decryption) time of each of the encryption algorithms due to the encryption key size, cipher block size of the encryption algorithms creates an added overhead on VoIP packets during VoIP transmission; this will have a clear effect on the QoS in terms of e2e delay and the rate at which packet are dropped depending on the Queue buffer and the jitter buffer algorithms. In today’s world where VoIP application users such as Skype, Apple Face Time are growing rapidly especially in the mobile platform sector and these users are competing with each other and other network devices for bandwidth, the need for selecting the best encryption algorithms and best mode of operation (stream/block cipher mode) with the highest threshold in terms of users in order to mitigate the cost of encryption on VoIP transmission and to effectively utilize the available network bandwidth cannot be over stated. This work is aimed at determining the threshold at which Quality of Service (QoS) will be affected when AES, DES, 3DES encryption algorithms are discretely implemented on the VoIP Crypto-Engine in stream or block cipher mode. This will be achieved by quantifying the overhead produced by stream and block ciphers in terms of latency (e2edelay) and rate of packet loss during a pre-established VoIP transmission. On the specifics, target objectives tend towards; achieving a clear review of related works that shed light on the cryptographic overheads accrued on real time applications such as VoIP. To achieve through critical analysis, the design of well-defined Test parameters for performing the simulated experiment covering parameters such codec, cipher, bandwidth, network topology. Determine through experimental simulation, the encryption (AES, DES, and 3DES) algorithms and the mode of encryption (stream/block mode) with the highest threshold point at which the QoS is affected in a VoIP call system. And finally to a resource pool for network and security computer society in
- 70. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 68 both academia and industry, for the adequate selection of the best encryption algorithms, the best mode of operation (stream/block), combined with the best voice codec’s for implementing in secure VoIP transmission. Because of the lack of security mechanism in Real-time Transport Protocol (RTP), Secure Real-time Transport Protocol (SRTP) was developed in 2004. SRTP employs the use of cryptographic algorithm and hash functions to provide confidentiality, integrity, authentication and anti-reply of data transmitted over RTP [5]. This discourse will focus strictly on the cryptographic algorithms used by SRTP. By default SRTP supports symmetric encryption algorithm for media transmission of the VoIP packet. VoIP packets are segmented into four sections the IP header, UDP header 8, RTP header and Payload. Packet size may be different depending on the voice codec used which determine the payload size; overall the packet header size is 40 bytes (IP header 20bytes, UDP header 8 bytes, and RTP header 12 bytes). Since SRTP encrypts the payload not header information our focus will be on the payload size. Although VoIP uses two main protocols; the signalling protocol and media transfer protocol, this work focuses on measuring the effect of encryption algorithms on media transfer protocols (RTP) only for pre-established VoIP transmission. Latency (e2eDelay), Packet Jitter and Packet Loss Ratio are the key network metrics used to determine the QoS of VoIP transmission. Precisely, only the effect of latency (e2eDelay) and the packet loss rate of the encryption algorithms will be determined. Encryption Algorithms to be covered include; Advance Encryption Standard (AES) with 128 bits key, Data Encryption Standard (DES) with 56 bits key and Triple Data Encryption Standard (3DES) with 56 bits key. The effects on latency and packet loss rate of the above listed encryption algorithms will be determined on G.711 and G.729 voice codec support VoIP network. 2. VOIP SECURITY: RELATED WORKS Voice over Internet Protocols (VoIP) is a technology that transmits real time data such as voice and (or) video over the internet [6]. In other words, VoIP provides a Public Switch Telephone Network (PSTN) or Circuit Switch Telephone Service over a Packet Switch system such as the Internet or Intranet [7]. In the traditional PSTN network, analog voice signals are transmitted over the network, this is not the case in VoIP. VoIP converts voice signals by the use of codec algorithms; codec’s converting the analog voice signals into digital packet, thus enabling voice signals to be transmitted over an IP-based network [8]. Unlike PSTN that supports a
- 71. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 69 dedicated end-to-end connection between the two end users, VoIP packet transmission does not require a directed channel, but rather employs UDP, which is a connectionless transport protocol. In VoIP, how the packets get from source to destination is not as important as the speed taken by packets to reach destination from the source [9]. VoIP supports the use of IP-phones (phones connected to the router), computer-to-computer communication, soft-phones (software based phones such Skype) and also in combination with PSTN or SIP-Based VoIP (internet/intranet), figure 1 shows a basic architecture of a VoIP system [10]. Figure 1: VoIP Architecture 1(VoIP 2005) Basically, two categories of protocols come functional in the operations of a VoIP system; signalling protocols and media transfer protocols. While signalling protocols help to ensure end-to-end connection and (or) disconnection between two end users [11] , the media transfer protocols aid the actualization of real-time voice and (or) video packet transmission [12] . 2.1 Security Mechanisms for VoIP It follows that by initial (default) design, both the signalling and media transfer protocols like SIP and RTP respectively have no security features attached, thus needing supporting protocols like SPD and RTCP respectively. This feature makes VoIP an easy target for attackers to eavesdrop on VoIP conversations and modify both the signalling and media transfer protocols [13] . In order to overcome these flaws, the three principles of security (Confidentiality, Integrity and Authentication) are implemented on both protocols.
- 72. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 70 2.1.1 Confidentiality This defines a concept protecting data or information from unauthorised accessed. It is achieved by encrypting the media transport protocols using symmetric encryption algorithms running in stream or block cipher modes to encrypt/decrypt VoIP packet or blocks of VoIP packets. SRTP was developed to provide RTP with a means of ensuring confidentiality. SRTP encrypts only the payload section of the VoIP packet, leaving the Header information (IP/UDP/RTP) section unencrypted [14]. All VoIP packets traffic are encrypted at source and decrypted at the destination by a Crypto- Engine. By way of elaboration, stream ciphers are a family of encryption algorithms where each bits on a plaintext such that M = m1+ m2+m3 are encrypted using a pseudorandom bits generated encryption key called a key stream such that K = k1 + K2 + k3 using a XOR Red operation such that EK(m) = Ek1 m1 k1=C1 to create a cipher C1 [15]. However, block ciphers are encryption algorithms that encrypt blocks of data at a time [16]; instead of one bit at a time like stream ciphers. Block ciphers segment the bits of plaintext into blocks usually a fixed size of 128 bits in the case of AES [17], but may differ with other ciphers. Using mode operation a random bits generated key is combined with bits from the previous successive ciphers to encrypt each block of data [18]. When used in VoIP, packets in blocks of128 bits of size for AES are encrypted and decrypted by the crypto-engine using a random key from each successive block of bits [19] , [20] . 2.1.2 Integrity This principle saves from unauthorised modification of data or information. The integrity of VoIP traffic is archived by the use of a Hash function algorithm. By default HMAC-SHA1 is used to ensure that VoIP packets have not been altered during transmission. Integrity is also implemented in VoIP when establishing a session in SIP. Typically, hashing the VoIP packet includes both the VoIP payload and the information Header. At the source end a hash value of RPT or SRTP VoIP packets is generated and the integrity is checked at the destination end by generating its own hash value and comparing it against the hash value of the received. 2.1.3 Authentication The security by Authentication feature used in VoIP is performed on the Session Protocols, in order to authenticate end-to-end establishment of VoIP session, asymmetric encryption algorithms are used. The two end users
- 73. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 71 negotiate a cipher suite to use in order to create a master key [14]. For instance, the SIP protocol doesn’t support any security mechanisms, but by the use of well-known, publically tested internet security mechanisms such as HTTP digests; it provides a mechanism for authenticating VoIP users. The authentication process can be hop-to-hop or end-to-end [21]. 2.2 VoIP Operation: Wired and Wireless Modes In a wired network scenario, VoIP system operates such that the user obtains an IP address from a DHCP server. The VoIP terminal (softphone) registers with a call server (PBX); where voice services access is granted after a completed registration process. For a call to be placed or received with the terminal device, the call server adds the registered device to a Domain Name System (DNS) server, thus enabling a directory lookup on an IP network. When Paul dials Alice, The destination number (Alice’s) is routed to a call server which in turns notifies the destination terminal (Alice). Once the destination terminal (Alice) accepts the call, a notification is sent back to the call server and the call server sends a notification to both terminals that a channel is available to start a conversation. However, the service flexibility in terms of mobility has seen wireless VoIP (VoIPoW) advancing farther than landline networks. VoIPoW enables mobile devices such as laptops, mobile phones, two way radios etc., to place and receive VoIP calls on a wireless network infrastructure either through Wireless LAN or Wireless WAN. Just like in VoIP wired landline network, in VoIPoW; the user terminal connects and registers with a call server by obtaining an IP address from a DHCP server, while SIP and RTP protocols supported by TCP/UDP helps the user to initiate and engage in a VoIP conversation by routing the compressed voice packet over a gateway to the destination user. Thus, VoIP employs the use of multiple protocols that support IP-based network, wired or wireless radio communication technology and other legacy communication systems such as PSTN and ISDN. It can also be deployed on a multitude of different architectures. For instance, Session Initiation Protocol (SIP) is a signalling protocol that is an application layer protocol on the TCP/IP network model which is based on request-response. It implies a client/server based architecture usually connecting two end users via a proxy server. The protocol is used to establish, terminate and modify sessions in VoIP over an IP based network [22]. SIP is also supported by Session Description Protocol (SDP); a protocol that carries the session descriptions such as session information and media information [23]. SDP is transmitted with the SIP packet during the first ‘INVITE’ packet and contains the session information that consists
- 74. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 72 of the session name and proposes the number of times the session is active, and the contact detail of the source of the session. The media information consists of type of media (voice/video) and the transport protocol information (RTP/UDP/IP). Real-time Transport Protocol (RTP) is another protocol-instance classified as a Media Transport Protocol. It comes useful when transferring real-time data such as voice or any media over the internet [24] either over a multicast or unicast network, and it is also supported by control protocol called Real- time Transport Control Protocol (RTCP). RTCP carries the description of the data packet being transmitted by RTP and is also used to determine the Quality of Service [25]. It contains information about the RTP packet such as; information about the users, and information that is used to measure Quality of Service parameters like number of packet loss and jitters. Both RTP and RTCP are designed to be completely independent from transport protocol (TCP/UDP) on the TCP/IP layer model [26]. 2.3 VoIP Security and QoS: Approaches and Shortcomings With relativity to VoIP Networks, quality of service (QoS) can be defined as the quality of voice/video during a VoIP transmission [27], and it is measured based on acceptable criteria’s set by international standard organizations like the International Telecommunication Union (ITU) and the Internet Engineering Task Force (IETF). In broader terms, network criteria for measuring service efficiency include; latency, packet loss and jitter. These too are applicable to VoIP. However, the economic constraint of an encryption algorithm on QoS depends on the encryption cipher and codec used [28]. In other words, the length of the encryption key and the mode of encryption (stream/block ciphers) combined with the processing time for encoding and decoding of the VoIP payload by the codec determines the budget on the QoS. Thus a logical solution to achieving our goal is to study the effect of voice codec when combined with the encryption algorithms and how they affect latency, packet loss and jitter during VoIP transmission. 2.3.1 Latency Latency or e2edelay in VoIP is the total round-trip delay time for a bi- directional VoIP packet transmission between two end users [29]. It can be measured in two ways; 250ms for a round-trip from source to destination and back to the source, or 150ms for one-way trip from source to destination, which also includes the delay time for the packet to travel along multiple hops over the internet as specified by the ITU-G 11.4 standards. It is calculated by defining three parameters in VoIP transmission; Dtransmitter,
- 75. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 73 Dnetwork, Dreceiver; where Delay is obtained by summing the three parameters [30]. The size of the encryption key and the mode of operation (stream/block) by the cipher algorithm will lengthen the encoding and decoding processes of the codec which will in turn increase the latency delay of the VoIP packet [19]. A study on the effect of DES/3DES/AES- 128-256, RC2 and Blowfish encryption algorithm on latency during a VoIP transmission using different bandwidths (34Kb, 64Kb) shows thus; when using 34kb bandwidth each of the encryption algorithms generate latency when compared with the use of firewall and without the use of firewall. Blowfish generates the highest latency with a time of 0.00001600 seconds. While a 64kb bandwidth, with or without a firewall generates almost the same latency with 3DES yielding the highest latency when compared with the other algorithms [31]. 2.3.2. Jitter Jitter defines the measured variation in each successive packet arrival time due to transmission delay [32]. This occurs when each successive packet have a different latency, since packets are transmitted over the network by the UPD transport protocol each packet will take a different pathway, and the arrival time will differ from source to destination A jitter buffer algorithm is used to assemble the packet but at the cost of time. If the packet cannot be reassembling within 150ms the packet is dropped. The acceptable level of jitter is about 20ms regardless of the number of multiple hops between the source and destination, if the time increases above 20ms the buffer cannot reassemble the packets in correct order making the conversation sound choppy [30]. The study of the impact of security mechanism on VoIP by measuring the effects on the encryption algorithms (3DES/AES-128-256/Blowfish and RC2 on 38k, 64k, 100M network bandwidths) on selected criteria as presented by (Talevski 2011) shows a high ratio of jitter on VoIP when there is no encryption and using a firewall while at 100M the jitter ratio is 0%. However, when using 38kb RC2 records the lowest ratio in comparison with 3DES, Blowfish, AES 128, AES 256 and DES. But when using 64k bandwidth RC2, AES 128, AES 256 and DES all yield lower ratios as compared with 3DES and Blowfish. Interestingly, when the bandwidth is 100Mbps there is no effect on the jitter on any of the encryption algorithms [33].
- 76. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 74 2.3.3. Packet loss This defines the ratio of packets dropped due to limited jitter buffer size at the destination end, or packets that did not reach their destination [34]. An acceptable percentage of packet loss should be below 5%, which includes multiple hops between source and destination of the VoIP transmission. When the packet loss is greater than 5% the destination end user will only hear air space. The study by [33] shows that using 38Kbps of bandwidth in all the encryption algorithms (3DES/AES-128-256/Blowfish and RC2), packet loss ratio is above the acceptable limit of 5% except for 3DES which yields 4% in 64Kbps of bandwidth. However, for 100Mbps speed, the packet of the algorithms is below or within the acceptable limit, with or without a firewall component attached. Therefore, it follows that the budget of encryption algorithm on QoS generally depends on the type of algorithm used, the length of the encryption key and the network bandwidth. The study presented above shows that only latency and packet loss bear negative impacts on the QoS. Its however amazing to note that the result of the two experiment show that encryption algorithms has a positive effect on the jitter of VoIP packets when compared to plain VoIP packet transmission; this might not be unconnected to network topology setup, since in all the test adopted a single point-to-point connection between the two computers there is no flexibility for VoIP packet taking multiple paths form source to destination The proliferation of varying VoIP applications with varying platform dependence necessitates a study for the determination of the economic constraints for the implementation of encryption on network performances and CPU cycle performances and the affect it will have on quality of voice or video between two end users. A comparative study of the effects of AES in both stream and block cipher modes on the QoS results relative to end-to-end delay between two end user [35]. The objectives of the study included; determining the errors generated by the two cipher modes when packets are decrypted at the destination end, and the effect of the errors on the QoS. Secondly, determining the effect of the two cipher modes on packet size, crypto-engine and packet loss on the QoS in terms of end-to-end delay. The authors used a GSM 06.10 Codec and AES algorithm for both stream and block mode to encrypt and decrypt RTP on the crypto-engine. The result showed that the packet size, crypto- engine and the packet loss all bear effects on the end-to-end delay between two end users. This outcome was further consolidated by [36], in his work. He worked on the effect of AES on packet size and the throughput of the crypto-engine when AES is operating on stream and block cipher mode.
- 77. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 75 Considering packet size scenario, his work showed that that each of the cipher mode has an effect on the packet size but AES operating on block cipher mode has a greater effect on packet size when compared to stream cipher mode, [36]. Considering crypto-engine, AES was used on the two cipher mode and the crypto-engine saturated by increasing the PPS by 25 PPS in every 30 seconds for each four (4) VoIP packet transmitted with the size of 60, 100, 250, and 100 for each of the four packets respectively. While focusing on packet size, the study proves that each of the cipher mode has an effect on the packet size but AES operating on block cipher mode has a greater effect on packet size when compared to stream cipher mode, the outcomes are shown in figures 2 and 3 [36]. The maximum threshold of the two cipher modes before the QoS is affected is indicated by a negative slope. In terms of packet loss, Mean Opinion Score (MOS) was used to evaluate the effect of packet loss on QoS of the two cipher modes on end-to-end delay. As would be noted, AES as stream cipher mode has less packet loss in end-to-end delay compared to block cipher mode, because of the use of key stream by stream ciphers. Summative, it implied that AES on stream cipher mode has a better performance than when run on block cipher mode that is before loss due to synchronization error [36]. Figure 2: Effects of Stream and Block Ciphers on packet size and throughput [36]
- 78. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 76 Figure 3: Packet Loss [36] In another related experiment by [37], the focus was on a family of block ciphers that uses linear prediction as mode of operation. The authors determined the threshold point at which the QoS will be affected based on VoIP traffic in terms of call volume. Using iterative block cipher to encrypt the VoIP packet in a simulated network environment the authors used IPsec for end-to-end transmission of VoIP packets with a total number of 600 users on the network. The users are interconnected using switches, routers and a state full firewall and G.729 codec with DES/3DES/AES encryption algorithms used in block cipher mode. VoIP packet with G.729 codec having a payload size of 10, 20, 30 and 40 bytes for encrypted VoIP packets using DES/3DES and 10 byte, 20 byte and 30 byte for plain VoIP packets were transmitted. The outcome showed that in plain VoIP traffic the packet loss started at about 160 calls when the payload is 10 bytes in size and the end-to-end delay is within the acceptable limit. QoS was unaffected probably due to compression or the reduction of the throughput by the codec and combined with the buffer and the FIFO algorithm used by the authors [37]. The end-to-end delay when encryption was applied was above 200ms which is beyond the acceptable limit. However, packet loss consideration revealed a three-time increase in the payload size; especially when the payload size is 10 bytes and also observed that the rate of packet loss is lower with increased payload size when using DES/3DES encryption algorithm. For
- 79. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 77 call volume traffic the study revealed that for all payload size when G.729 codec is used with DES/3DES; the rate of packet loss will be above the acceptable loss limit [38]. The works reviewed took differing approaches for answering the question ‘which algorithm is better in terms of the effect on the QoS of the VoIP network?’ The outcomes are quite similar with respect to latency, packet loss with each laying emphasis on direct relation between latency, packet loss, and jitter to the type of encryption algorithm in the crypto-engine, the cipher mode of operation, length of the encryption key and the payload size (codec). However, they both bear varied strengths and limitations that basically tended towards methodology, topology and parameters. While the former used a point-to-point network connection between the two hosts; which restricted the results to only VoIP in a peer-to-peer network, and focused on the use of only AES encryption algorithms, without considerations to other encryption algorithms like DES, 3DES, Blowfish, etc. The latter simulated a real world application of VoIP network with routers, switches, and firewall but whose result is only restricted to encryption algorithms running on block cipher modes only. 3. MODEL SIMULATION This covers a detailed overview of the experiment test-bed and the simulation parameters that will be used to evaluate the effects of encryption algorithms on QoS; when implemented in Stream and Block ciphers mode to secure VoIP communication. The methodology for performing the experiment and the simulation parameters will all be implemented in NS2 network simulation environment. Such parameters as the VoIP codec, the type of encryption algorithms, the length of the encryption key, the mode of encryption (Stream or Block cipher mode), the network topology and the type of transport protocols (UPD/TCP), the media transfer protocol (RTP) and the network bandwidth will be considered. The comprehensive simulation parameters setup is captured in table 1. 3.1 Simulation Parameters As noted earlier, the key components that constitute the basis for secure SIP-Based VoIP transmission include; voice codec, encryption algorithms, and networking properties such as bandwidth, propagation delay of the network links, queue type and size [39]. Thus, these will be used for the simulation. Table 1 shows the details of the simulation setup as would be used.
- 80. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 78 3.2 Simulation Scenario The simulation is divided into two phases; phase A involves conducting an experiment with the defined encryption parameters using G.711 voice codec parameter following the process presented in figure 4, while phase B follows the same process, only this time using G.729 voice parameters. As seen on figure 4, A TCL script is initiated containing networking parameters, voice codec parameters and encryption parameters in NS2. Each of the voice codec is run against the three encryption algorithms (AES, DES, 3DES) in stream or Block cipher mode. The effect of each of the encryption algorithm on the QoS when operating in stream or block cipher mode will be evaluated, and the effect on the QoS will be measured in terms of e2edelay and packet loss rate. An analysis of the collected data will be made, the analysed data will be measured against the acceptable standard define in ITU standards. 1) AES Scenario The first simulation scenario involves evaluating the cost of AES encryption when implemented in stream or block cipher mode in securing VoIP traffic. The cost of AES encryption with 128 bits key on QoS when used in combination with G.711 and G.729 codec’s is quantified by measuring the latency (end2end one way delay) of VoIP packet from source to destination as shown in the figure 5. The figure indicates that simulations will run for 10 minutes, in each successful minute of the simulation ten nodes having two-way VoIP transmission will be initiated. Each VoIP packet during the transmission will be encrypted with AES encryption algorithm.
- 81. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 79 Table 1: Simulation Setup Statistics Value Test Platform Ubuntu Virtual Machine Simulator NS2 Number of scenarios 3 Number of Nodes 100 Number of domains 4 Nodes per domain 25 (To simulate the different geographical locations covering the study. Network Properties Bandwidth Speed (Optional) 2Mbps Queue Type Drop Tail Queue Size 50 Propagation Delay 10ms Simulation Parameters Voice Codec G.711 G.729 Encryption Algorithm AES (Key length 128 Bits, Block size 128 bits) DES (Key length 56 Bits, Block size 64 bits) 3DES (Key length 168 Bits, Block size 64 bits) Traffic Test Metrics - End-to-End Delay - Packet Loss Simulation Scenarios - AES Scenario - DES Scenario - 3DES Scenario
- 82. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 80 e Figure 4: Simulation Blueprint. The AES simulation will be sub-divided into two experiments in which AES will run on Stream cipher mode and again run on Block Cipher mode. In each of the cipher modes G.711 and G.729 VoIP codec will be encrypted. Using the volume of VoIP traffic, the threshold point at which the QoS will be affected with respect to the two cipher modes will be determined. The criteria that will be used to measure the effect on the QoS are; end2end delay and the rate of packet loss when the number of VoIP traffic is increased in each successful 1minute of the 10 minutes of the simulation.
- 83. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 81 Figure 5: AES Simulation Scenario 2) DES Scenario This involves using DES encryption algorithm with 54 bits encryption key and 64 bits block size to encrypt the VoIP packet. G.711 and G.729 codecs will also be used in a similar scenario as depicted in figure 5. Adopting the similarities, DES simulation will run for 10 minutes, in each successful minute of the simulation, ten nodes each having two-way VoIP transmission will be initiated with each VoIP packet during the transmission encrypted with DES 54 bit encryption key algorithm. The scenario is also segmented into two experiments in which DES runs on Stream cipher mode and on Block Cipher mode, with each of the cipher modes utilizing G.711 and G.729 VoIP codecs in encrypted forms. Using the volume of VoIP traffic, the threshold point at which the QoS will be affected in respect to the two cipher mode will be determined. Similar criteria as the AES are also adopted here for the simulation timeline. 3) 3DES Scenario This third simulation adopts Triple DES (3DES) encryption algorithms to encrypt VoIP traffic. Akin to DES in the second simulation, 54 bits encryption key length and 64 bit block size will be used in combination with
- 84. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 82 G.711 and G.729 codecs, with a simulation runtime of 10 minutes. In each successful minute of the simulation, ten nodes having a two-way VoIP transmission will be initiated with each VoIP packet during the transmission encrypted with 3DES 54 bit encryption key algorithm. And just like the prior tests, 3DES will run on both Stream cipher and Block Cipher modes with each of the cipher modes utilizing G.711 and G.729 VoIP codecs in encrypted form. All other criteria similar to prior test. 4. RESULTS AND ANALYSIS. Based on defined parameters for the study, focused is directed on the threshold point at which the QoS of active VoIP calls exceed the acceptable limits as a result of overheads created by each encryption algorithms in stream and block cipher mode during VoIP transmission. Figure 6: AES using G.711 (64Kbps) in Stream and Block Cipher mode
- 85. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 83 Figure 7: Packet Loss Rate for AES using G.711 (64Kbps) |G.729 (8Kbps) 4.1 AES E2E Delay and Packet Loss Rate Comparing the effects on e2e delay and packet loss rate for AES (128 bits) operating in stream and block cipher modes on G.711 (64Kbps) and G.729 (8Kbps). The implementation of AES (128 bits) in stream cipher mode performs better and faster when compared with AES (128 bit) in block cipher mode as shown in figure 6. The results shows that AES (128 bits) in stream mode has a higher threshold point before the e2e delay exceeds the acceptable standard defined by ITU with 40 VoIP calls for encrypted VoIP traffic and 30 VoIP calls for plain VoIP traffic which are about 200ms and 150ms respectively. AES (128 bits) in block cipher on G.711 (64Kbps) has a lower threshold point with 20 VoIP calls for encrypted VoIP traffic with 200ms and 10 VoIP calls for plain VoIP traffic with 150ms respectively. Similarly, AES (128 bits) using G.729 (8Kbps) on stream and block ciphers modes shows parallel results with G.711 (64Kbps) both in stream mode and block cipher mode. On the other hand, results show that AES using G.729 (8Kbps) codec in stream mode perform better in block mode, with a threshold of 40 VoIP calls for encrypted VoIP traffic which is 201ms and 30 VoIP calls for plain VoIP traffic which is 155ms, and in block cipher mode the threshold of 20 VoIP calls for encrypted VoIP traffic which is 200ms and 15 VoIP calls for plain VoIP calls which is 150ms. The high threshold of AES (128 bits) in stream cipher mode on both G.711 (64Kbps) and G.729 (8Kbps) codecs can be directly linked to, how stream ciphers encrypt and decrypt data using an XORed operation, in which each bits of data is encrypted using a key stream. The voice codec delay, the network propagation delay, network bandwidth and the FIFO queue buffer
- 86. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 84 at each particular time of the simulation are also a major contributing factor to the increase in e2e delay in each of the cipher modes. Considering the rate of packet loss for AES (128 bits) with G.711 (64Kbps) and G.729 (8Kbps), results as shown in figure 7 shows that AES (128 bits) in both G.711 (64Kbps) and G.729 (8Kbps) codecs on stream and block cipher mode has a drastic effect on the rate of packet loss. Although the results indicates that AES (128 bits) in stream cipher mode has a lowest packet loss rate when compared with AES (128 bits) in block cipher mode which yields 40 VoIP calls before the acceptable packet loss rate of 5% is exceeded . While in block cipher mode yields a threshold of 25 VoIP calls before 5% packet loss rate is exceeded. For G.729 (8Kbps) codec, it indicates that AES (128 bits) has little significant difference in stream and block cipher mode with respect to packet loss rate. Specifically, AES (128 bits) in stream mode has a threshold of 22 VoIP calls before the packet loss rate exceeds 5%, and a threshold of 12 VoIP calls in block mode. Increase in packet size, and FIFO queue algorithms on each of the routers all contribute to the rate of packet loss. 4.2 DES E2E Delay and Packet Loss Rate Looking at the effect of DES (56 bits) on e2e delay and packet loss rate using G.711 (64Kbps) and G.729 (8Kbps) codecs, results show that the implementation of DES (56 bits) in stream cipher mode performs better and faster when compared with block cipher mode. DES (56 bits) in stream mode yields a higher threshold point before the e2e delay exceeds the acceptable limit with 40 VoIP calls for encrypted VoIP traffic and 25 VoIP calls for plain VoIP traffic which are about 200ms and 150ms respectively, compared to the block mode which yields a threshold point with 25 VoIP calls for encrypted VoIP traffic with 200ms and 15 VoIP calls for plain VoIP traffic with 150ms respectively. Correspondingly, DES (56 bits) with G.729 (8Kbps) on stream and block cipher shows similar results with G.711 (64Kbps) both in stream mode and block mode as shown in figure 8. Threshold variations are linked to how stream ciphers encrypt and decrypt data using a XORed operation, in which each bits of data is encrypted using a key stream. All other contributors to delay and specifically, discontinuous e2e delay remain the same as in AES scenario. For rate of packet loss on G.711 (64Kbps) and G.729 (8Kbps) codec with DES (56 bits) encryption, results in figure 9 show that DES (56 bits) in both G.711 (64Kbps) and G.729 (8Kbps) on stream and block cipher mode has a sweeping outcome on the rate packet loss. On G.711 (64Kbps), DES (56 bits) in stream cipher mode has a less packet loss rate when compared with
- 87. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 85 DES (56bits) in block cipher mode with 20 VoIP calls before the acceptable packet loss rate of 5% is exceeded. While in block cipher mode, the threshold point at which the acceptable packet loss rate exceeds 5% is at 15 VoIP calls. While On G.729 (8Kbps), it indicates that DES (56 bits) has no significant difference in stream and block cipher mode with respect to packet loss rate, this is because the rate of packet loss of the two cipher mode is drastic in less than 10 VoIP calls for acceptable packet loss of 5%; all other conditions remaining unchanged as with AES (128bits). Figure 8: DES with G.729 (8Kbps) in Stream and Block Cipher mode Figure 9: Packet Loss Rate for AES with G.711 (64Kbps) |G.729 (8Kbps)
- 88. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 86 Figure 70: 3DES with G.711 (64Kbps) in Stream and Block Cipher mode Figure 81: Packet Loss Rate for AES with G.711 (64Kbps) |G.729 (8Kbps) 3DES E2E Delay and Packet Loss Rate Underscoring the effects of 3DES on e2e delay and packet loss rate using G.711 (64Kbps) and G.729 (8Kbps) codec, the outcome shows that 3DES (56 bits) in stream cipher and block cipher mode has no significant difference as shown in figure 10. The difference can only be noticed when the number of VoIP calls exceeds 40 calls. 3DES (56 bits) in both stream and block cipher mode on G.711 (64Kbps) all yield a threshold point of 20 VoIP calls encrypted VoIP traffic with 200ms and 10 VoIP calls for plain VoIP traffic with 150ms in stream mode, the results for block cipher mode was not farfetched. 3DES (56 bits) with G.729 (8Kbps) on stream and block cipher show similar results with G.711 (64Kbps) both in stream mode and block mode. The low threshold of 3DES (56 bits) in stream and block cipher mode on both G.711 (64Kbps) and G.729 (8Kbps) can be directly
- 89. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 87 linked to the large computational time required to encrypt and decrypt bits and blocks of data. For the rate of packet loss for DES (56 bits) with G.711 (64Kbps) and G.729 (8Kbps), 3DES (56 bits) in both G.711 (64Kbps) and G.729 (8Kbps) on stream and block cipher mode has a far-reaching outcome on the rate of packet loss. This is shown in figure 11. On G.711 (64Kbps), the results indicates that 3DES (56 bits) in both stream and block cipher mode packet loss rate are negligible between the two cipher modes; with each of the cipher mode exceeding 5% packet loss at about 5 VoIP calls. However, using G.729 (8Kbps); the results indicates that 3DES (56 bits) has no significant difference in stream and block cipher modes with respect to packet loss rate. This is because the rate of packet loss of the two cipher mode is drastic in less than 5 VoIP calls for acceptable packet loss of 5%. 5. CONCLUSION AND FUTURE WORKS The results of the simulations shows that using AES (128 bits) and DES (56 bits) in stream cipher mode yields a better and faster performance compared to when implemented in block cipher using G.711(64Kbps) and G.729(8Kbps) codec’s supported VoIP network. Whereas in 3DES there are no significant differences in stream or block cipher when implemented using G.711 (64Kbps) and G.729 (8Kbps) supported VoIP networks. Truthfully, cryptographic algorithms and hash functions are used to guarantee confidentiality, authentication, and integrity and anti-replay of VoIP packets. However the use of cryptographic algorithms on real time applications such as VoIP comes with a cost in terms of delay and increase in packet size, which is due to the processing time required encrypted and decrypt VoIP packets before transmission at the source and after transmission at the destination. Couple of components on the VoIP system like voice codec, Jitter buffer algorithms, routers queue size and the network bandwidth all impose transmission delays, which apparently pose performance and productivity setbacks to VoIP service providers and developers. When all this delay factors are combined with the cryptographic delay there will be a point at which latency and rate of packets loss due to the cryptographic delay and increase in packet size will have a negative effect on the QoS of active calls. Undoubtedly, the results of the study strongly indicates that each of the encryption (AES, DES, 3DES) algorithms append an additional overhead on the e2e delay and rate of packet loss during VoIP transmission. However
- 90. International Journal ofComputer Science and Business Informatics IJCSBI.ORG ISSN: 1694-2108 | Vol. 15, No. 1. JANUARY 2015 88 when calculating and comparing the overhead of each of the three encryption algorithms, it demonstrates that AES and DES (in stream cipher mode on G.711 (64Kbps) and G.729 (8Kbps). VoIP support codec are faster and have a higher threshold in terms of number of calls before the e2e delay and the rate of packet loss exceeds the acceptable limit for encrypted and plain VoIP e2e delay and packet loss rate. The simulation also implies that there no significant difference in both e2e delay and packet loss rate for 3DES in stream and block ciphers modes on G.711 (Kbps) and G.729 (8Kbps) VoIP supported codec, this is because 3DES has a drastic effect both the e2e delay and packet loss rate at similar number of calls. Although the study only focuses at measuring the effects of stream and block ciphers on VoIP in terms of e2e delay and the rate of packet loss during VoIP transmission. It did not address the issues of the effect of Synchronization and Bit Explanation errors generated by stream and block ciphers respectively. Future work can tend towards measuring the cost of errors generated by both cipher modes on pre-established VoIP transmission. REFERENCES [1] B Boguhn. (2009, June) A Compare Business Products Web site. [Online]. http://www.comparebusinessproducts.com/phone-systems/business-voip/voip-named- as-fastest-growing-technology-of-the-past-decade. [2] N Wittenberg. (2009) Understanding Voice Over IP Technology, Cengage Learning. Document. [3] D J Wright. (2001) Voice over packet networks. Document. [4] O Hersent, IP Telephony: Deploying VoIP Protocols and IMS Infrastructure.: John Wiley & Sons, 2010. [5] M Leggieri and E Gambi, "Quality assessment of secure VoIP communications," in 16th International Conference on Software, Telecommunications and Computer Networks, 2008. SoftCOM 2008, 2008. [6] J Fischl and H Tschofenig, "Making SIP Make Cents ," Queue, vol. 5, no. 2, pp. 42- 49, 2007. [7] C Shiping and W Xinyuan, "On the anonymity and traceability of peer-to-peer VoIP calls," Network, vol. 20, no. 5, pp. 32-37, 2006. [8] A S.W Marzuki and C Yu Ka, "Performances analysis of VoIP over 802.11b and 802.11e using different CODECs," in 2010 International Symposium on Communications and Information Technologies (ISCIT), 2010. [9] N Sulaiman and R Carrasco, "Performance Evaluation of Voice Call over an IP based Network," in 41st Annual Conference on Information Sciences and Systems, 2007. CISS '07, 2007. [10] M B VoIP. (2005) A Business Voip Website. [Online]. http://mybusinessvoip.com/what-is-voip [11] K K Tam and H L Goh, "Session Initiation Protocol," in IEEE International
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