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International Journal of Innovation Engineering and Science Research
Open Access
Volume 2 Issue 3 May 2018 1 | P a g e
ABSTRACT
Probabilistic Polling System Approach for IoT
Secure Routing
Seyed Mahmood Hashemi
Beijing University of Technology
Beijing, CHINA
The Internet of things (IoT) affects on humans life deeply. There are traditional cyber threats and also new
threats. There is no guard and immunity for systems against the innumerable variance of attack and exploitation.
In this paper, an approach base on Polling System is presented for secure routing IoT devices. We use polling
system with probabilistic routing, so there is a probability to move from one queue to another. Probabilistic polling
system allows us to perform priority of stakeholders’ votes.
Keywords- Internet of Things; Secure Routing; Polling System
I. INTRODUCTION
The Internet of things (IoT) affects on humans life deeply [9]. Although the new IoT functionality of
smart devices causes to the better life for the human, there are traditional cyber threats and also new
threats. However there were many works on the IoT security, most of them were not Use-Centric. In
against of the previous works, the proposed approach is base on the interaction with users, so it is
User-Centric completely. In a broad view, we divide IoT networks into two categories: 1- consumer and
2- industrial. While we use IoT devices in a smart home, we emphasize on the smart point of the IoT
devices. In other words, the ideal point of IoT devices is communicated and adjusting to other physical
devices in the home. While a set of smart home devices has a particular behavior or need for special
decision making, we called them as user-centric IoT (UCIoT) [10].
There is no guard and immunity for systems against the innumerable variance of attack and
exploitation. Thus security mechanism has fought to keep with IoT. Intelligence is successful to detect
the intruder. IoT has the challenge to bridge physical with the cyber world [11]. Previous security
mechanisms must be adapted in order to maintain defensive expectation.
In this paper, an approach base on Polling System is presented for secure routing IoT devices. In the
classical view, Polling System is a set of one server and multiple queues. Clients are arrived and set
into queues and then get server according to a particular policy. (figure 1)
Seyed Mahmood Hashemi “International Journal of Innovation Engineering and Science Research”
Volume 2 Issue 3 May 2018 2 | P a g e
Fig. 1. Classical Polling System
The number of queues and also the capacity of queues are predefined. In the beginning, Polling
System is used for the time-sharing computer system, but now it is used to model wide variety
applications (computer communications, robotics, traffic and transportation, manufacturing, production,
mail distribution, etc.) [12, 13, 14]. In the time-sharing polling system, there are N terminals that are
connected to a central computer. The central computer visit terminals in turn and cyclic order. The size
of queues is finite and the arrival process is independent Poisson Process with parameter λi.
Several service policies are examined on the basic model of Polling System such as exhaustive, gated,
and limited-I policies. The server policy determines association server to clients. The basic Polling
model can be applied in different applications: Token Ring Networks; Robotic Systems; Various Non-
Generic Computers; Communication Systems. The common scheme for Polling System is a server
resource shared by multiple queues. The basic model of Polling System is cyclic polling model. In the
next step, the fixed polling order is replaced with random polling order. The important measure of the
performance of Polling System is Response Time [15, 16]. In the Polling System with probabilistic
routing, when the client in queue i is serviced, it is routed to queue j with probabilitypi,j.
In this paper, we use polling system with probabilistic routing. Polling system provides a platform for
security voting of all stakeholders. In the other side, probabilistic routing establishes priority approach.
Therefore the presented approach can be used in the organization with employees by different priority.
This paper is organized as follow: section 2 is the study of related works; section 3 explains proposal
algorithm, finally, section 4 is the conclusion.
II. RELATED WORKS
Akatyev et. Al. assume heterogeneous IoT devices. they use data flow diagram to represent the
dependencies between users and information [1, 20]. In [2, 21, 22], In this survey, authors categorize
IoT security issues into three groups: 1- low-level security issues; 2- intermediate-level security issues
and high-level security issues and then study about security mechanism for each of them. Coulter et.
al. research in current intrusion detection approaches from an intelligence perspective.
Levy et. al.define different types of polling systems [4, 23, 24]. Time-sharing polling system, there are N
terminals that are connected to a central computer. The central computer visit terminals in turn and
cyclic order. The size of queues is finite and the arrival process is independent Poisson Process with
parameter λi. In [5], Authors use a M/M/1 queue to model the traffic of the network. Yang et. al.
propose an approach to estimate the mean queue length, mean cycle time and throughout for two-
class priority-based polling system. Tags energy conservation is the top priority in RFID systems.In a
SERVER
𝑄 𝑁
𝑄1 𝑄2
𝑄3
Seyed Mahmood Hashemi “International Journal of Innovation Engineering and Science Research”
Volume 2 Issue 3 May 2018 3 | P a g e
typical RFID, which has one or multiple readers and numerous tags, each tag (carrier identifier) is
communicated directly to readers. Tags, base on battery consumption, are divided into two groups: 1-
active and 2- passive. Passive tags do not have an internal battery and instead of it, they are used
radio waves. While there are many warehouse products whit own tags, passive tags cause to
interference and sophisticated communication. Active tags against passive tags have own battery-
powered and can be used in mobile status. [7] presents an approach to design an efficient protocol for
active tags. Cyber-Physical Systems (CPS) are set of different devices include computational,
networked, communicational and sensor devices [8, 18, 19]. CPS can be used for monitor, control and
in general wireless communication. CPS architecture has three layers: 1- Cyber layer, 2- physical layer
and 3- Networking layer.
Fig. 2. Security Levels
Since inefficient utilization of bandwidth, deterministic Multi-Access Control (MAC) protocols are not
adapted to the requirements of CPS. In a polling MAC protocol, request to transmit data packets are
done base on the density of in polling list. Zheng et. al. design a polling MAC protocol to meet the
requirements of CPS applications. In that protocol, authors use Orthogonal Frequency Division
Multiplexing (OFDM), which is the contention of IEEE 802.11 [8, 16].
Previous works specified two points: 1-using polling system to gather different opinions and 2-apply
priority in polling system to different users.
III. 3 PROPOSED ALGORITHM
The data packets need to route while they are transferred via the network. There are different
parameters to select a suitable path. In the other side, there are different stakeholders that have
opinions to transfer a data packet. In the simplest situation, there is SERVER on the one side and there
is CLIENT on the other side. The most route approaches concern some special formulas. Although
their approach is common and usable, the users' opinions are ignored. Proposed algorithm concerns
Physical Layer
Networking Layer
Cyber Layer
Sensors and Actuators
Analysis and Decision
Seyed Mahmood Hashemi “International Journal of Innovation Engineering and Science Research”
Volume 2 Issue 3 May 2018 4 | P a g e
users’ opinions, indeed it considers the priority of stakeholders. Actually, all stakeholders do not have
same expertise, so there must be a difference between stakeholders.
In this paper, users decide about a suitable path. The users take their opinions about the feasible paths
(as votes) and then the suitable path is decided base on votes. In the proposed algorithm, there is a
queue for voting users. Users can give their vote in this queue, and also their position can rise to the
next queue according to the following probability:
p = an a1 + ⋯+ am
(1
While a1 + ⋯ + am are coefficients of queues and set as default. a means coefficient of nth queue.
Coefficients are sorted ascend to descend, so the probability to raise positions of stakeholders reduces
in each epoch of algorithm.
Above probability is used just when there is no pre-knowledge of stakeholders, but if there is pre-
knowledge for priority of stakeholders, it can be applied without probability. When all stakeholders are
assigned in queues, the final vote is calculated by adding votes in different queues multiply their
coefficients.
Let assign coefficients as follow:
a = 8 6 5 4
(2
There are 20 stakeholders in the system and four queues, so the probability of queues are as:
p1 = 0.34, p2 = 0.26, p3 = 0.21 p4 = 0.21
(3
IV. 4 CONCLUSION
In this paper, an approach base on Polling System is presented for secure routing IoT devices. Polling
System is used because one important parameter for secure routing is stakeholders' opinions. Since
there is a difference between the positions of stakeholders, we use probabilistic polling system. In
presented system, clients in queues are visited (voting policy) according to a probability. Actually, we
can change the voting policy or set some clients as constant in some queues. There is need to pre-
knowledge to set the constant position of clients, but there is an opportunity for this job in the paper.
REFERENCES
[1] Nikolay Akatyev, Joshua I. James, “Evidence identification in IoT networks based on threat assessment”, ELSEVIER,
Future Generation Computer Systems.
[2] Minhaj Ahmad Khan, Khaled Salah, “IoT security: Review, block chain solutions, and open challenges”, ELSEVIER,
Future Generation Computer Systems.
[3] Rory Coulter, Lei Pan, “Intelligent agents defending for an IoT world: A review”, ELSEVIER, computers & s e c u r i t y
73 ( 2 0 1 8 ) 439–458
[4] HANOCH LEVY, MOSHE SIDI, “Polling Systems : Applications, Modeling, and Optimization”, IEEE TRANSACTIONS
ON COMMUNICATIONS. VOL. 38, NO. 10, OCTOBER 1990
[5] JIANG Wei, TIAN Zhihong, CAI Chao, GONG Bei, “Bottleneck Analysis for Data Acquisition in High-Speed Network
Traffic Monitoring”, NETWORK TECHNOLOGY AND APPLICATION
[6] Zhijun Yang, Hongwei Ding, “Characteristics of a Two-Class Polling System Model”, TSINGHUA SCIENCE AND
TECHNOLOGY, ISSNll1007-0214ll11/13llpp516-520, Volume 19, Number 5, October 2014
[7] Yan Qiao, Shigang Chen, Tao Li, Shiping Chen, “Tag-Ordering Polling Protocols in RFID Systems”, IEEE/ACM
TRANSACTIONS ON NETWORKING, VOL. 24, NO. 3, JUNE 2016
[8] Meng Zheng, Junru Lin, Wei Liang, Haibin Yu, “A Priority-aware Frequency Domain Polling MAC Protocol for OFDMA-
based Networks in Cyber-physical Systems”, IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 2, NO. 4,
OCTOBER 2015
Seyed Mahmood Hashemi “International Journal of Innovation Engineering and Science Research”
Volume 2 Issue 3 May 2018 5 | P a g e
[9] Anita Vorster, Les Labschagne, “A Framework for Comparing Different Information Security Risk Analysis
Methodologies”, ACM, Proceeding of SAICSIT 2005, pp. 95-103
[10] Jakub Breier, Ladislav Hudec, “Risk Analysis Supported by Information Security Metrics”, ACM, International
Conference on Computer Systems and Technologies, CompSysTech’11, 2011
[11] Januszkiewicz Paulina, Pyka Marek, “Designing a Security Policy According to BS 7799 Using the OCTAVE
Methodology”, IEEE, Second International Conference on Availability, Reliability and Security (ARES'07), 2007
[12] Johannes Viehmann, “Reusing Risk Analysis Results, An Extension for the CORAS Risk Analysis Method”, IEEE,
International Conference on Social Computing, 2012
[13] Li-Xin Wang, “a course in fuzzy system and control”, Prentice-Hall International, Inc., pp. 4-7, 1997
[14] Nan Feng, Harry Jinnan Wang, Minqiang Li, “A security risk analysis model for information system: Casual relationships
of risk factors and vulnerability propagation analysis”, ELSEVIER, Information Sciences 256 (2014) 57-73
[15] Maisa Mendonca Silva, Ana Paula Henriques de Gusmão, Thiago Poleto, Lúcio Camara e Silva, Ana Paula Cabral
Seixas Costa, “A multidimensional approach to information security riskmanagement using FMEA and fuzzy theory”,
ELSEVIER, International Journal of Information Management 34 (2014) 733–740
[16] L. Klienrock, H. Levy, “the analysis of random polling systems”, Operation Research Society of America, 1998
[17] A. Wierman, E. M. M. Winands, O. J. Boxama, “scheduling in polling systems”, ELSEVIER, 2007
[18] W. Bux, “local-area subnetworks: a performance comparison”, IEEE, Transaction on Communications, 29(10):1465-
1473, 1981
[19] T. Li, D. Logothetis, M. Veeraraghavan, “analysis of a polling system for telephony traffic with application to wireless
LANs”, IEEE, transaction on wireless communications, Vol. 5, No. 6, 2006
[20] J. A. Weststrate, “analysis and optimization of polling systems”, PhD thesis, Tilburg University, 1992
[21] D. Gupta, M. M. Srinivasan, “polling systems with state-independent setup times”, Queueing Systems, 22:403-423,
1996
[22] J. A. Weststrate, “analysis and optimization of polling systems”, PhD thesis, Tilburg University, 1992
[23] A. Federgruen, Z. Katalan, “costumer waiting-time distributions under base-stock policies in single facility multi-item
production systems”, Naval Research Logistics, 43:533-548, 1996
[24] A. Federgruen, Z. Katalan, “the stochastic economic lot scheduling problem: cyclical base-stock policies with idle times”,
Management Science, 44:989-1001, 1996

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Probabilistic Polling System Approach for Prioritizing IoT Secure Routing

  • 1. International Journal of Innovation Engineering and Science Research Open Access Volume 2 Issue 3 May 2018 1 | P a g e ABSTRACT Probabilistic Polling System Approach for IoT Secure Routing Seyed Mahmood Hashemi Beijing University of Technology Beijing, CHINA The Internet of things (IoT) affects on humans life deeply. There are traditional cyber threats and also new threats. There is no guard and immunity for systems against the innumerable variance of attack and exploitation. In this paper, an approach base on Polling System is presented for secure routing IoT devices. We use polling system with probabilistic routing, so there is a probability to move from one queue to another. Probabilistic polling system allows us to perform priority of stakeholders’ votes. Keywords- Internet of Things; Secure Routing; Polling System I. INTRODUCTION The Internet of things (IoT) affects on humans life deeply [9]. Although the new IoT functionality of smart devices causes to the better life for the human, there are traditional cyber threats and also new threats. However there were many works on the IoT security, most of them were not Use-Centric. In against of the previous works, the proposed approach is base on the interaction with users, so it is User-Centric completely. In a broad view, we divide IoT networks into two categories: 1- consumer and 2- industrial. While we use IoT devices in a smart home, we emphasize on the smart point of the IoT devices. In other words, the ideal point of IoT devices is communicated and adjusting to other physical devices in the home. While a set of smart home devices has a particular behavior or need for special decision making, we called them as user-centric IoT (UCIoT) [10]. There is no guard and immunity for systems against the innumerable variance of attack and exploitation. Thus security mechanism has fought to keep with IoT. Intelligence is successful to detect the intruder. IoT has the challenge to bridge physical with the cyber world [11]. Previous security mechanisms must be adapted in order to maintain defensive expectation. In this paper, an approach base on Polling System is presented for secure routing IoT devices. In the classical view, Polling System is a set of one server and multiple queues. Clients are arrived and set into queues and then get server according to a particular policy. (figure 1)
  • 2. Seyed Mahmood Hashemi “International Journal of Innovation Engineering and Science Research” Volume 2 Issue 3 May 2018 2 | P a g e Fig. 1. Classical Polling System The number of queues and also the capacity of queues are predefined. In the beginning, Polling System is used for the time-sharing computer system, but now it is used to model wide variety applications (computer communications, robotics, traffic and transportation, manufacturing, production, mail distribution, etc.) [12, 13, 14]. In the time-sharing polling system, there are N terminals that are connected to a central computer. The central computer visit terminals in turn and cyclic order. The size of queues is finite and the arrival process is independent Poisson Process with parameter λi. Several service policies are examined on the basic model of Polling System such as exhaustive, gated, and limited-I policies. The server policy determines association server to clients. The basic Polling model can be applied in different applications: Token Ring Networks; Robotic Systems; Various Non- Generic Computers; Communication Systems. The common scheme for Polling System is a server resource shared by multiple queues. The basic model of Polling System is cyclic polling model. In the next step, the fixed polling order is replaced with random polling order. The important measure of the performance of Polling System is Response Time [15, 16]. In the Polling System with probabilistic routing, when the client in queue i is serviced, it is routed to queue j with probabilitypi,j. In this paper, we use polling system with probabilistic routing. Polling system provides a platform for security voting of all stakeholders. In the other side, probabilistic routing establishes priority approach. Therefore the presented approach can be used in the organization with employees by different priority. This paper is organized as follow: section 2 is the study of related works; section 3 explains proposal algorithm, finally, section 4 is the conclusion. II. RELATED WORKS Akatyev et. Al. assume heterogeneous IoT devices. they use data flow diagram to represent the dependencies between users and information [1, 20]. In [2, 21, 22], In this survey, authors categorize IoT security issues into three groups: 1- low-level security issues; 2- intermediate-level security issues and high-level security issues and then study about security mechanism for each of them. Coulter et. al. research in current intrusion detection approaches from an intelligence perspective. Levy et. al.define different types of polling systems [4, 23, 24]. Time-sharing polling system, there are N terminals that are connected to a central computer. The central computer visit terminals in turn and cyclic order. The size of queues is finite and the arrival process is independent Poisson Process with parameter λi. In [5], Authors use a M/M/1 queue to model the traffic of the network. Yang et. al. propose an approach to estimate the mean queue length, mean cycle time and throughout for two- class priority-based polling system. Tags energy conservation is the top priority in RFID systems.In a SERVER 𝑄 𝑁 𝑄1 𝑄2 𝑄3
  • 3. Seyed Mahmood Hashemi “International Journal of Innovation Engineering and Science Research” Volume 2 Issue 3 May 2018 3 | P a g e typical RFID, which has one or multiple readers and numerous tags, each tag (carrier identifier) is communicated directly to readers. Tags, base on battery consumption, are divided into two groups: 1- active and 2- passive. Passive tags do not have an internal battery and instead of it, they are used radio waves. While there are many warehouse products whit own tags, passive tags cause to interference and sophisticated communication. Active tags against passive tags have own battery- powered and can be used in mobile status. [7] presents an approach to design an efficient protocol for active tags. Cyber-Physical Systems (CPS) are set of different devices include computational, networked, communicational and sensor devices [8, 18, 19]. CPS can be used for monitor, control and in general wireless communication. CPS architecture has three layers: 1- Cyber layer, 2- physical layer and 3- Networking layer. Fig. 2. Security Levels Since inefficient utilization of bandwidth, deterministic Multi-Access Control (MAC) protocols are not adapted to the requirements of CPS. In a polling MAC protocol, request to transmit data packets are done base on the density of in polling list. Zheng et. al. design a polling MAC protocol to meet the requirements of CPS applications. In that protocol, authors use Orthogonal Frequency Division Multiplexing (OFDM), which is the contention of IEEE 802.11 [8, 16]. Previous works specified two points: 1-using polling system to gather different opinions and 2-apply priority in polling system to different users. III. 3 PROPOSED ALGORITHM The data packets need to route while they are transferred via the network. There are different parameters to select a suitable path. In the other side, there are different stakeholders that have opinions to transfer a data packet. In the simplest situation, there is SERVER on the one side and there is CLIENT on the other side. The most route approaches concern some special formulas. Although their approach is common and usable, the users' opinions are ignored. Proposed algorithm concerns Physical Layer Networking Layer Cyber Layer Sensors and Actuators Analysis and Decision
  • 4. Seyed Mahmood Hashemi “International Journal of Innovation Engineering and Science Research” Volume 2 Issue 3 May 2018 4 | P a g e users’ opinions, indeed it considers the priority of stakeholders. Actually, all stakeholders do not have same expertise, so there must be a difference between stakeholders. In this paper, users decide about a suitable path. The users take their opinions about the feasible paths (as votes) and then the suitable path is decided base on votes. In the proposed algorithm, there is a queue for voting users. Users can give their vote in this queue, and also their position can rise to the next queue according to the following probability: p = an a1 + ⋯+ am (1 While a1 + ⋯ + am are coefficients of queues and set as default. a means coefficient of nth queue. Coefficients are sorted ascend to descend, so the probability to raise positions of stakeholders reduces in each epoch of algorithm. Above probability is used just when there is no pre-knowledge of stakeholders, but if there is pre- knowledge for priority of stakeholders, it can be applied without probability. When all stakeholders are assigned in queues, the final vote is calculated by adding votes in different queues multiply their coefficients. Let assign coefficients as follow: a = 8 6 5 4 (2 There are 20 stakeholders in the system and four queues, so the probability of queues are as: p1 = 0.34, p2 = 0.26, p3 = 0.21 p4 = 0.21 (3 IV. 4 CONCLUSION In this paper, an approach base on Polling System is presented for secure routing IoT devices. Polling System is used because one important parameter for secure routing is stakeholders' opinions. Since there is a difference between the positions of stakeholders, we use probabilistic polling system. In presented system, clients in queues are visited (voting policy) according to a probability. Actually, we can change the voting policy or set some clients as constant in some queues. There is need to pre- knowledge to set the constant position of clients, but there is an opportunity for this job in the paper. REFERENCES [1] Nikolay Akatyev, Joshua I. James, “Evidence identification in IoT networks based on threat assessment”, ELSEVIER, Future Generation Computer Systems. [2] Minhaj Ahmad Khan, Khaled Salah, “IoT security: Review, block chain solutions, and open challenges”, ELSEVIER, Future Generation Computer Systems. [3] Rory Coulter, Lei Pan, “Intelligent agents defending for an IoT world: A review”, ELSEVIER, computers & s e c u r i t y 73 ( 2 0 1 8 ) 439–458 [4] HANOCH LEVY, MOSHE SIDI, “Polling Systems : Applications, Modeling, and Optimization”, IEEE TRANSACTIONS ON COMMUNICATIONS. VOL. 38, NO. 10, OCTOBER 1990 [5] JIANG Wei, TIAN Zhihong, CAI Chao, GONG Bei, “Bottleneck Analysis for Data Acquisition in High-Speed Network Traffic Monitoring”, NETWORK TECHNOLOGY AND APPLICATION [6] Zhijun Yang, Hongwei Ding, “Characteristics of a Two-Class Polling System Model”, TSINGHUA SCIENCE AND TECHNOLOGY, ISSNll1007-0214ll11/13llpp516-520, Volume 19, Number 5, October 2014 [7] Yan Qiao, Shigang Chen, Tao Li, Shiping Chen, “Tag-Ordering Polling Protocols in RFID Systems”, IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 24, NO. 3, JUNE 2016 [8] Meng Zheng, Junru Lin, Wei Liang, Haibin Yu, “A Priority-aware Frequency Domain Polling MAC Protocol for OFDMA- based Networks in Cyber-physical Systems”, IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 2, NO. 4, OCTOBER 2015
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