Article

Article title THE METHOD OF RESISTANCE TO ACTIVE ATTACKS IN WIRELESS SENSOR NETWORKS
Authors A.S. Basan, E.S. Basan, О.B. Makarevich
Section SECTION I. INFORMATION TECHNOLOGIES AND PROTECTION OF INFORMATION
Month, Year 05, 2017 @en
Index UDC 004.056: 004.73
DOI
Abstract The purpose of the research is to develop methods and systems which can effectively detect active attacks of intruders based on the analysis of wireless and network parameters of wireless sensor networks (WSN). Analysed are the physical indicators which can be attacked by an intruder. Developed is the method for detecting a malicious node with physical characteristics of the network. The developed method is based on the use of probability functions, the calculation of the confidence interval and the probability of deviation of current indicators from the confidence interval. The novelty of the method is that when a malicious action is detected, the distribution of the current state is not compared with the reference distribution, and its influence in the confidence interval is also estimated. In addition, the novelty of the method is that it contains analytical tools for detecting an intruder, as well as methods for detecting attacks (IDS), based on methods of analyzing only network traffic. The advantage is that in mobile WSN there is a high probability of not only network attacks, but also attacks aimed at violation of physical activity (violation of movement of nodes, exhaustion of energy resources, and transmission of packages). A mobile wireless sensor network has been simulated. A series of attacks on mobile WSN are given. The effectiveness of using the developed method, compared to analogues, is evaluated. Having analysed the parameters of residual energy and congestion of the node we succeeded in expanding the range of attacks the network is able to counter in comparison with the analogs of the system. These attacks include "denial of service" attacks, "Sibyll attack", "resource depletion attacks".

Download PDF

Keywords Attack, attack detection, security, wireless sensor networks, trust, probabilistic methods.
References 1. Abramov E.S., Basan E.S. Razrabotka modeli zashchishchennoy klasternoy besprovodnoy sensornoy seti [Development of a model of a protected cluster wireless sensor network], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2013, No. 12 (149), pp. 48-56.
2. Basan E.S., Makarevich O.B., Abramov E.S. Razrabotka sistemy obnaruzheniya atak dlya klasternoy besprovodnoy sensornoy seti [Development of a system for detecting attacks for a cluster wireless sensor network], Informatsionnoe protivodeystvie ugrozam terrorizma [Infor-mation Counteraction to Terrorism Threats], 2013, No. 20, pp. 134-140.
3. Govindan K., Mohapatra P. Trust computations and trust dynamics in mobile adhoc networks, A survey IEEE Communications Surveys & Tutorials, No. 14 (2), pp. 279-298.
4. Abramov E.S., Basan E.S. Analiz stsenariev atak na besprovodnye sensornye seti [Analysis of attack scenarios for wireless sensor networks], Materialy XIII Mezhdunarodnoy nauchno-prakticheskoy konferentsii «IB–2013» [Proceedings of XIII International scientific-practical con-ference "Information security 2013"]. Part 1. Taganrog: Izd–vo TTI YuFU, 2012, pp. 60-65.
5. Shelukhin O.I., Simonyan A.G., Ivanov Yu.A. Osobennosti DDoS atak v besprovodnykh setyakh [Features of DDoS attacks in wireless networks], T–Comm – Telekommunikatsii i Transport [T–Comm – Telecommunications and Transport], 2012, No. 11, pp. 67-71.
6. Bel'fer R.A., Ogurtsov I.C. Zashchita informatsionnoy bezopasnosti sensornoy seti klasternoy arkhitektury s pomoshch'yu mekhanizma obnaruzheniya vtorzheniya [Protection of information security, sensor network cluster architecture is a mechanism for intrusion detection], Vestnik MGTU im. N.E. Baumana: elektronnoe izdanie [Herald of the Bauman Moscow State Technical University: electronic edition], 2013, pp. 1-7.
7. Deepali Virmani, Manas Hemrajani, Shringarica Chandel. Exponential Trust Based Mecha-nism to Detect Black Hole attack in Wireless Sensor Network, International Journal of Soft Computing and Engineering (IJSCE), 2014, pp. 14-16.
8. Grishechkina T.A. Analiz atak na setevye protokoly v mobil'nykh sensornykh setyakh Ad Hoc [Analysis of attacks in mobile Ad Hoc networks using vulnerabilties in network protocols], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2012, No. 12 (137), pp. 68-74.
9. Basan A.S., Basan E.S., Makarevich O.B. Methodology of Countering Attacks for Wireless Sensor Networks Based on Trust.2016, International Conference on Cyber–Enabled Distrib-uted Computing and Knowledge Discovery, pp. 409-4012.
10. Basan A.S., Basan E.S., Makarevich O.B. Development of the Hierarchal Trust management System for Mobile Cluster–based Wireless Sensor Network, Proceeding SIN '16 Proceedings of the 9th International Conference on Security of Information and Networks, 2016, pp. 116-122.
11. Abramov E.S., Basan E.S. Razrabotka zashchishchennogo protokola upravleniya mobil'noy klasternoy sensornoy set'yu [Developing a secure management Protocol for mobile cluster sen-sor network], Informatsionnoe protivodeystvie ugrozam terrorizma [Information Counteraction to Terrorism Threats], 2014, No. 23 (23), pp. 46-51.
12. Abramov E.S., Basan E.S., Makarevich О.B. Development of a secure Cluster–based wireless sensor network model, SIN’13. Proceedings of the 6th International Conference on Security of Information and Networks – November 26–28 2013, Aksaray, Turkey, pp. 372-375.
13. Abramov E.S., Basan E.S. Razrabotka nabora metrik dlya vybora glavy klastera v mobil'noy sensornoy seti [Develop a set of metrics to select the cluster head in mobile sensor networks], Informatsionnoe protivodeystvie ugrozam terrorizma [Information Counteraction to Terrorism Threats], 2014, No. 23 (23), pp. 52-55.
14. Teplitskaya S.N., Khuseyn Ya.T. Energeticheski effektivnyy algoritm samoorganizatsii v besprovodnoy sensornoy seti [Energetically effective algorithm of self–organization in a wireless sensor network], Vostochno-Evropeyskiy zhurnal peredovykh tekhnologiy [East–European Journal of Advanced Technologies], 2012, No. 2/9 (56), pp. 25-29.
15. Mohammad Momani. Bayesian Fusion Algorithm for Inferring Trust in Wireless Sensor Net-works, Journal of Networks, 2010, No. 5 (7), pp. 815-822. DOI: 10.4304/jnw.5.7.815–822.
16. Elmar Schoch, Michael Feiri, Frank Kargl, Michael Weber. Simulation of Ad Hoc Networks: ns–2 compared to JiST/SWANS // SIMUTools. Marseille, France, 2008.
17. Shelby Z., Bormann C. 6LoWPAN: The Wireless Embedded Internet, Wiley Series on Com-munications Networking & Distributed Systems, 2010, pp. 245.
18. Basan A.S., Basan E.S., Makarevich O.B. Programma analiza dannykh i vychisleniya doveriya v besprovodnoy sensornoy seti. Svidetel'stvo o gosudarstvennoy registratsii programmy dlya EVM №2016615606, 2016 g. [Program data analysis and computing of trust in wireless sensor networks. The certificate of state registration of computer programs №2016615606, 2016].
19. Abramson N. The Throughput of Packet Broadcasting Channels, IEEE Transactions on Com-munications, 1977, Vol. 25, No. 1, pp. 117-128.
20. Ho J.W. Zone–based trust management in sensor networks, in IEEE International Conference on Pervasive Computing and Communications, 2009, pp. 1-2.
21. Renjian Feng, Xiaona Han, Qiang Liu, and Ning Yu. A Credible Bayesian–Based Trust Management Scheme for Wireless Sensor Networks, Hindawi Publishing Corporation International Journal of Distributed Sensor Networks, pp. 1-9. DOI: http://dx.doi.org/10.1155/2015/678926.
22. Chen–xu Liu, Yun Liu, and Zhen–jiang Zhang. Improved Reliable Trust–Based and Energy–Efficient Data Aggregation for Wireless Sensor Networks, Hindawi Publishing Corporation International Journal of Distributed Sensor Networks Volume 2013, pp. 1-11. DOI: http://dx.doi.org/10.1155/2013/652495.
23. Ganeriwal S., Balzano L.K., and Srivastava M.B. Reputationbased framework for high integrity sensor networks, ACM Trans. Sen. Netw., 2008, Vol. 4, No. 3, pp. 1-37.

Comments are closed.