Current Trends in Information Technology vol 6 issue 3

INFORMATION TECHNOLOGY
Current Trends in
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1. Hadoop and Map Reduce for Simplified Processing of Big Data
Shobha Rani 1
2. Big Data to Big Data Mining: Issues, Challenges and Data Analytics Solutions
Neeraj Kumar, Madhulika Pandey, Krishan Kumar 7
3. Group Management for Secure and Dynamic Sharing of Data in Cloud Computing
Raju Dara, Bhongir Sony 16
4. Public Auditing Based Detection of Packet Dropping Attacks in Wireless Ad Hoc Networks
Raju Dara, Srikanth Ravula 24
5. Double Guard: Detection Intrusion in Multitier Application
S.D. Jadhav, S.R. Nallewar, N.V. Burande, G.V. Bawaskar, R.D. Shilpakar 32
6. Protected Data Compilation in WSN Using Random Routing Algorithms
Raju Dara, Jellela Satish Reddy 43
Contents

CTIT(2016) 1-6 © STM Journals 2016. All Rights Reserved Page 1
Volume 6, Issue 3
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Hadoop and Map Reduce for Simplified Processing of
Big Data
Shobha Rani*
Department of Computer Science, Akarapu Sharath Chandrika Devi Memorial College for Women,
Warangal, Telangana, India
Abstract
Big data refers to large and complex data sets made up of a variety of structured and
unstructured data, which are too big, too fast, or too hard to be managed by traditional
techniques. Hadoop is an open source software platform for structuring big data on computer
clusters built from commodity hardware and enabling it for data analysis. It is designed to
scale up from a single server to thousands of machines, with a very high degree of fault
tolerance. MapReduce is a programming model for processing large data sets with parallel
distributed algorithm on cluster. This paper presents the survey of simplified big data
processing with Hadoop architecture and MapReduce framework.
Keywords: Big data, Hadoop, MapReduce, HDFS, Big data Analytics
INTRODUCTION
Currently, enormous amounts of data are
created every day. With the rapid expansion of
data, we are moving from the terabyte to the
petabyte Age. At the same time, new
technologies make it possible to organize and
utilize the massive amounts of data currently
being generated. However, this trend creates a
great demand for new data storage and analysis
methods [1, 2]. Especially, theoretical and
practical aspects of extracting knowledge from
massive data sets have become quite important.
The term “Big Data” has recently been applied
to datasets that grow so large and become
unsuitable to work with the traditional database
management systems. They are data sets whose
size is beyond the ability of commonly used
software tools and storage systems to capture,
store, manage, as well as process data within a
tolerable elapsed time [3]. Big data sizes are
constantly increasing, currently ranging from
terabytes to petabytes of data in a single data
set. Consequently, some of the problems related
to big data include data capture, store,
searching, sharing, analysis and visualization.
Today enterprises are exploring large volumes
of highly detailed data so as to discover facts
they did not know before [4].
 Ambiguity—a lack of metadata creates
ambiguity in big data that leads to
inconsistency (Figure 1).
 Viscosity—measure of data flow over the
network.

Volume 6, Issue 3
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Big Data to Big Data Mining: Issues, Challenges and Data
Analytics Solutions
Neeraj Kumar, Madhulika Pandey*, Krishan Kumar
Department of Computer Science, JIMS Engineering Management Technical Campus, Greater Noida,
Uttar Pradesh, India
Abstract
Data has evolved at a great pace due to increasing interest of people and valuable
contribution towards the emerging technologies. Emerging technologies are successful in
generating huge quantity of data from various sources which in return provides Big Data. Big
Data constitutes large amount of data in terms of texts, statistics, facts, figures, and records,
etc., generated from heterogeneous environment. Big Data needs special attention for storage,
managing, transportation and processing of data. It includes amassing of data in terms of
3V’s, i.e. volume, variety and velocity. Issues and challenges of Big Data are real time
obstacles and needs instant consideration. This paper presents the overview of Big Data along
with its issues and challenges. Applications of data mining in Big Data along with some of its
open sources are also discussed in the paper.
Keywords: Big Data, big data analytics, big data mining, Massive Online Analysis, R,
GraphLab, Pegasus, Mahout
INTRODUCTION
In the pre-digital revolution world of the late
1980s, most of the data was stored on
videotapes such as VHS cassettes, Vinyl LP
records, audio cassette tapes, and photography
accounted for significant portions as well.
Paper based storage represented 33% of all the
data storage on its own in 1986. 25 % of all
the data stored in the world in 2000 was stored
digitally. 2002 was the first year in which
digital storage capacity overtook analog
capacity. The digital storage grew annually by
23% between 1986 and 2007 with 94 % of all
the data was stored in digital format by 2007
[1]. Now, we are successful in generating and
collecting data from numerous sources.
The data volumes are exploding. Today, more
than 2.5 exabytes (2.5 billion gigabytes) of
data is generated every single day. This is
expected to continue growing at a significant
rate with mobile devices accounting for much
of this data. Every second we create new data.
For example, we perform 40,000 search
queries every second (on Google alone), which
makes it 3.5 searches per day and 1.2 trillion
searches per year. Facebook users send on
average 31.25 million messages and view 2.77
million videos every minute [2]. Applications
of internet, such as E-commerce, social
networking sites, etc., are speeding up the data
generation process, this type of data generated
and gathered in huge volume is ‘Big Data’.
Big Data is making its valuable place in global
economy as it is turning into driving force for
economy. As data is increasing day by day, so
with the increase of size of data it is difficult
to manage such huge volume with the current
technology. Data is collected from various
sources because of which it is heterogeneous
in nature and may be deficient as well. There
is a need to store, manage and process the data
with innovative technology that can handle
and make use of data and transform it into
meaningful data, i.e. information.
This information from data is analyzed using
new techniques for generating valuable
outcomes useful for organizations and
businesses (Figure 1). This holds importance in
knowledge discovery and decision support
system. The data management of Big Data is
beyond the capability of classic database or
computer system. Big Data Analytics are the
one who generates valuable outcomes from

CTIT (2016) 16-23 © STM Journals 2016. All Rights Reserved Page 16
Volume 6, Issue 3
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Group Management for Secure and Dynamic Sharing of
Data in Cloud Computing
Raju Dara, Bhongir Sony*
Department of Computer Science Engineering, Krishna Murthy Institute of Technology and
Engineering, Jawaharlal Nehru Technological University, Hyderabad, Telangana, India
Abstract
Cloud computing has emerged as new model of computing which allows outsourcing data.
The phenomenon of outsourcing data to cloud became obvious as cloud has infrastructure as
a service (IaaS) layer for it. With this feature of cloud, there is growing trend in outsourcing
data to cloud. When an enterprise outsources its data to cloud, it needs to take care of its
functionalities in terms of data sharing across its users. The company creates groups and
manages group members in order to have secure and dynamic data sharing. Group manager
is responsible to determine data to be shared and privileges of group members. Group
management is very dynamic thing where new users may be added and existing members may
be removed from group. The users who are not associated with the group may involve in
collusion attack. The existing systems focus on group management and data sharing. In this
paper, we built a mechanism for revoking a user and disable all credentials given to him. We
built a prototype application that demonstrates the proof of concept. The empirical results
revealed that the proposed scheme is effective.
Keywords: Cloud computing, outsourcing, group management, secure data sharing, user
revocation
INTRODUCTION
Cloud computing became a reality. This is in
fact the latest technology that enables the
world to have a shared pool of resources and
access the resources through internet. This
phenomenon works for users without making
capital investment. The users of cloud can gain
access to resources and pay as they use. This is
very useful to computing community as the
cloud resources are made available to all
without restrictions. As the data is growing
exponentially, the enterprises prefer
outsourcing data to cloud for reducing
expenses and ease of management. However,
the cloud is treated as untrusted environment.
That is the reason there is security concern
while outsourcing data to cloud. Cloud can
also be used to store and share data to other
users. Cloud services are shown in Figure 1.
In this context, the data may be associated
with different groups in the cloud assuming
that an enterprise has multiple groups of
people working on different projects. In this
case, data is associated with groups. The data
of one group is not accessible to other group.
There is group manager who is responsible to
manage data and group members. Group
members may be added or removed as
required. The group manager is responsible to
handle security issues also. Group manager
can grant or remake privileges to group
members. The problem with such system is
that when users are removed from the group,
their access credentials are misused by people
to make collusion attacks. In this paper, we
proposed a user revocation scheme that takes
care of perfect user revocation process. With
user revocation, it is possible that the old
credentials cannot be misused and thus the
collusion attack is prevented. In this paper, our
contribution is to have a secure and dynamic
scheme for data sharing in cloud and it is
equipped with user revocation scheme for
complete security. The remainder of the paper
is structured as follows: next part of the paper
provides review of literature. After that, the
proposed system is presented in detail,
followed by experimental results and the
conclusion.

Volume 6, Issue 3
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Public Auditing Based Detection of Packet Dropping
Attacks in Wireless Ad Hoc Networks
Raju Dara, Srikanth Ravula*
Abstract
Wireless ad hoc networks are vulnerable to packet dropping attacks. However, they are also
subjected to packet dropping due to link errors. In case of multi-hop wireless networks, it is
essential to differentiate packet dropping due to link error or malicious attack. When any
mechanism is able to differentiate this, can provide high level of security to the network with
respect to packet dropping attacks. Many solutions came into existence as found in the
literature. In this paper, we considered a special insider attack where malicious nodes are
aware of other nodes in the network and exploit their knowledge to achieve packet drop which
is potential risk in communication networks. Achieving satisfactory accuracy in detection of
packet loss due to malicious attacks is given high importance. In this paper, public auditing
mechanism is proposed and implemented that exploits correlations between lost packets. We
proposed a public auditing architecture for accurate detection of packet drop attacks. We
built a custom simulator using Java platform to demonstrate the proof of concept. The
empirical results reveal the usefulness of the proposed system.
Keywords: Wireless ad hoc network, packet dropping, auditing
INTRODUCTION
Network is made up of number of nodes. Each
node in the network can act as information
sender and information receiver. It is true in
case of multi-hops between sender and
receiver. The sender may not be able to send
packets directly to destination without the
cooperation from intermediate nodes on the
way. Therefore, it is essential to have such
cooperation. Having understood this, there are
certain issues here. The intermediate nodes
may act as malicious nodes and drop packets
without forwarding to neighbours.
In wireless ad hoc networks, this is the
problem that needs to be addressed. As
packets play a vital role in communication,
dropped packets cannot provide meaningful
information to destination. This way the
communication quality is deteriorated. With
respect to delay, insensitive packets pertaining
to a live event, it is important to ensure that
packets are reaching destination accurately.
Thus there is need for dealing with this
problem in order to have meaningful
communications in communication networks.
The existing applications either focused on
packet dropping caused by link errors or
attacks. Many existing mechanisms simply
consider packet dropping due to attacks. They
do not differentiate packet loss due to link
error and packet loss due to an attack. In this
paper we proposed a public auditing based
solution, which demonstrates the proof of
concept. The system is implemented in the
form of a custom simulator developed using
Java platform. The empirical results revealed
that the proposed system is able to
differentiate between packet losses due to link
error from that caused by malicious attacks.
The remainder of the paper is structured as
follow: next part of the paper provides review
of literature, presentation of the proposed
system in detail, experimental results and after
that, the conclusion of the paper.
RELATED WORKS
Malicious packet drops and packet drops due
to link errors is the differentiation shown by
detection algorithms generally. High malicious
dropping rates and low link errors in one
pattern. The second pattern is high link errors

Volume 6, Issue 3
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Double Guard: Detection Intrusion in Multitier
Application
S.D. Jadhav*, S.R. Nallewar, N.V. Burande, G.V. Bawaskar, R.D. Shilpakar
Department of Information Technology, Dhole Patil College of Engineering, Wagholi, Pune,
Maharashtra, India
Abstract
In double guard intrusion in multitier system, it is important concept taking into account
attacks. There is very little work being performed on multi-tiered anomaly detection (AD)
systems. It generates models of network behavior for both web and database network
interactions. In such multi-tiered architectures, the back-end database server is often
protected in system behind a firewall, while the web servers are remotely over the internet.
Though they are protected from direct remote attacks, the back-end systems are susceptible to
attacks that use web requests as a means to exploit. It detects this type of attack since the web
IDS would merely see typical user login traffic. The current multi-threaded web server
architecture in this system carries multiple systems; it is not feasible to detect or profile such
causal mapping between web server traffic and it has deserver traffic, since traffic cannot be
clearly attributed to user sessions in the use.
Keywords: Attacks, double guard, IDS, SQL, TCP
INTRODUCTION
Problem Definition
In this project we present double guard, a
system used to detect various attacks in multi-
tiered web services and our approach can
create normality models of isolated user
sessions that include both, the web front end
(HTTP) and back end (File or SQL) network
transactions [1]. To achieve this, we employ a
lightweight virtualization technique to assign
each user’s web session to addicted container,
an isolated virtual computing environment.
We use the container ID to accurately
associate the web request with the subsequent
DB queries. Double guard can build a causal
mapping profile by taking both, the in web
server and DB traffic into account in the
system used [2].
Objective
Intrusion detection system currently examines
network request individually within both, the
web server and the database system. However,
there is very little work being performed on
multi-tiered anomaly detection systems that
generate models of network behavior for both,
back end and web server database interactions.
The back end database server is often protected
behind a firewall while the web servers are
remotely accessible over the internet. Attacks
that use web request as a means to exploit the
back end and are very important.
Need of Project
Attacks like Sql and DDoS are very much
severe. These attacks in the past have affected
the system many number of times. These types
of attacks are not recognized by antivirus or by
firewalls. Hence, a system that can recognize
and deflect these attacks is required.
LITERATURE SURVEY
Of all the papers referred to implement the
proposed system, systems similar to the one
proposed here and on which we attempt to
present improvements on, can be espied in
three of the research papers [1–3].
We have successfully applied static program
analysis to intrusion detection and our
approach is automatic: the programmer or
system administrator merely needs to run our
tools on the program at hand. All other
automatic approaches to intrusion detection to
date have been based on statistical inference,
leading to many false alarms; in contrast, our

Volume 6, Issue 3
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Protected Data Compilation in WSN Using Random
Routing Algorithms
Raju Dara, Jellela Satish Reddy *
Abstract
Wireless sensor networks make it conceivable to send secure information from source to
destination. On the off chance that connected to network checking information on a host, they
can be used to distinguish bargained hub; and refusal of administration is two-key assault. In
this paper, we display four "Multi-way randomized directing Algorithm", a technique to send
the information, various approaches to order the information into wireless sensor systems.
The pure random propagation, shares are engendered in view of one-bounce neighborhood
data, sink TTL beginning worth N in every offer and remaining calculations enhance the
effectiveness of shares in light of utilizing two-jump neighborhood data. Our work ponders the
best calculation by distinguishing the included hubs with dark gaps and refusal of
administration in the bundle data with multipath directing calculations that has not been
utilized some time recently. We investigated the calculation that have the best proficiency and
depicts the proposed framework.
Keywords: Wireless sensor networks, security, attacks and routing
INTRODUCTION
Wireless sensor networks normally comprise
of high cost, low-control, and multifunctional
wireless sensor hubs, with detecting wireless
correspondence capacities [1, 2]. These sensor
hubs impart the separation by means of a
wireless medium and work together to fulfill a
typical undertaking, for instance, environment
checking, military reconnaissance, and
mechanical procedure control (Figure 1) [3].
The fundamental reasoning behind WSNs is
that, while the ability of every individual
sensor hub is constrained, the total force of the
whole system is adequate for the required
mission.
In numerous WSN applications, the
organization of sensor hubs is performed in an
especially appointed manner without watchful
arranging and designing. Once sent, the sensor
hubs must have the capacity to self-ruling, and
sort out themselves into a wireless
correspondence system. Sensor hubs are
battery-controlled and are relied upon to work
without participation for a generally drawn out
stretch of time.
Most of the time it is extremely troublesome
and even difficult to change or revive batteries
for the sensor hubs. WSNs are portrayed with
denser levels of sensor hub, lack of quality of
sensor hubs, and separate force, calculation,
and memory limitations. In this way, the kinds
attributes and requirements present numerous
new difficulties for the advancement and use
of WSNs.
Wireless sensor system (WSN) is a
heterogeneous framework joining a large
number of small, modest sensor hubs with a
few recognizing qualities. It is low handling
force and radio reaches, allowing low vitality
utilization in the sensor hubs, and performing
constrained and particular detecting and
observing capacities [1–6].
Notwithstanding WSNs structure, a specific
class of specially appointed systems that work
with little base and have pulled in scientists for
its improvement and numerous potential
regular citizen and military applications, for
example, ecological observing, combat zone
reconnaissance, and country security. Be that
as it may, outlining security conventions is a

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