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A Game Theory Based Multi Layered Intrusion Detection Framework for Wireless Sensor Networks

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Abstract

Most of the existing intrusion detection frameworks proposed for wireless sensor networks (WSNs) are computation and energy intensive, which adversely affect the overall lifetime of the WSNs. In addition, some of these frameworks generate a significant volume of IDS traffic, which can cause congestion in bandwidth constrained WSNs. In this paper, we aim to address these issues by proposing a game theory based multi layered intrusion detection framework for WSNs. The proposed framework uses a combination of specification rules and a lightweight neural network based anomaly detection module to identify the malicious sensor nodes. Additionally, the framework models the interaction between the IDS and the sensor node being monitored as a two player non-cooperative Bayesian game. This allows the IDS to adopt probabilistic monitoring strategies based on the Bayesian Nash Equilibrium of the game and thereby, reduce the volume of IDS traffic introduced into the sensor network. The framework also proposes two different reputation update and expulsion mechanisms to enforce cooperation and discourage malicious behavior among monitoring nodes. These mechanisms are based on two different methodologies namely, Shapley Value and Vickery–Clark–Grooves (VCG) mechanism. The complexity analysis of the proposed reputation update and expulsion mechanisms have been carried out and are shown to be linear in terms of the input sizes of the mechanisms. Simulation results show that the proposed framework achieves higher accuracy and detection rate across wide range of attacks, while at the same time minimizes the overall energy consumption and volume of IDS traffic in the WSN.

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References

  1. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, Wireless sensor networks: A survey, Computer Networks, Vol. 38, No. 4, pp. 393–422, 2002.

    Article  Google Scholar 

  2. Y. Wang, G. Attebury and B. Ramamurthy, A survey of security issues in wireless sensor networks, IEEE Communications Surveys Tutorials, Vol. 8, No. 2, pp. 2–23, 2006.

    Article  Google Scholar 

  3. H. M. Salmon, C. M. de Farias, P. Loureiro, L. Pirmez, S. Rossetto, P. H. de A. Rodrigues, R. Pirmez, F. C. Delicato and L. F. R. da Costa Carmo, Intrusion detection system for wireless sensor networks using danger theory immune-inspired techniques, International Journal of Wireless Information Networks, Vol. 20, No. 1, pp. 39–66, 2013.

    Article  Google Scholar 

  4. K. Deng and Z. Liu, Minimum path exposure and detection interval setting for target detection using wireless sensor network, International Journal of Wireless Information Networks, Vol. 14, No. 4, pp. 289–294, 2007.

    Article  Google Scholar 

  5. L. Zhou and H. C. Chao, Multimedia traffic security architecture for the internet of things, IEEE Network, Vol. 25, No. 3, pp. 35–40, 2011.

    Article  Google Scholar 

  6. M. A. S. Jr, P. S. Barreto, C. B. Margi and T. C. Carvalho, A survey on key management mechanisms for distributed wireless sensor networks, Computer Networks, Vol. 54, No. 15, pp. 2591–2612, 2010.

    Article  Google Scholar 

  7. A. Abduvaliyev, A.-S. Pathan, J. Zhou, R. Roman and W.-C. Wong, On the vital areas of intrusion detection systems in wireless sensor networks, IEEE Communications Surveys Tutorials, Vol. 15, No. 3, pp. 1223–1237, 2013.

    Article  Google Scholar 

  8. I. Butun, S. D. Morgera and R. Sankar, A survey of intrusion detection systems in wireless sensor networks, IEEE Communications Surveys Tutorials, Vol. 16, No. 1, pp. 266–282, 2014.

    Article  Google Scholar 

  9. R. J. Aumann, R. B. Myerson, The Shapley and Value: Essays in Honor of Lloyd S. Shapley, ch. Endogenous Formation of Links between Players and of Coalitions: An Application of the Shapley Value, 1988. pp. 175–191.

  10. A. Mas-Colell, M. Whinston and J. Green, Microeconomic Theory, Oxford University PressOxford, 1995.

    MATH  Google Scholar 

  11. R.-C. Chen, C.-F. Hsieh, and Y.-F. Huang, A new method for intrusion detection on hierarchical wireless sensor networks. In Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication, pages 238–245, 2009. ACM.

  12. C.-C. Su, K.-M. Chang, Y.-H. Kuo and M.-F. Horng, The new intrusion prevention and detection approaches for clustering-based sensor networks wireless sensor networks. In IEEE Wireless Communications and Networking Conference, vol. 4, pages 1927–1932, 2005. IEEE.

  13. H. Sedjelmaci, S. M. Senouci and M. Feham, An efficient intrusion detection framework in cluster-based wireless sensor networks, Security and Communication Networks, Vol. 6, No. 10, pp. 1211–1224, 2013.

    Google Scholar 

  14. I. Krontiris, Z. Benenson, T. Giannetsos, F. C. Freiling and T. Dimitriou, Cooperative intrusion detection in wireless sensor networks. In Proceedings of the 6th European Conference on Wireless Sensor Networks, pages 263–278, 2009. Springer.

  15. A. P. R. da Silva, M. H. T. Martins, B. P. S. Rocha, A. A. F. Loureiro, L. B. Ruiz and H. C. Wong, Decentralized intrusion detection in wireless sensor networks. In Proceedings of the 1st ACM International Workshop on Quality of Service&Amp; Security in Wireless and Mobile Networks, pages 16–23, 2005. ACM.

  16. E. C. H. Ngai, J. Liu and M. R. Lyu, On the intruder detection for sinkhole attack in wireless sensor networks. In IEEE International Conference on Communications, vol. 8, pages 3383–3389, 2006. IEEE.

  17. S. S. Doumit and D. P. Agrawal, Self-organized criticality and stochastic learning based intrusion detection system for wireless sensor networks. In Proceedings of the 2003 IEEE Conference on Military Communications, pages 609–614, 2003. IEEE Computer Society.

  18. S. Rajasegarar, C. Leckie, M. Palaniswami and J. C. Bezdek, Quarter sphere based distributed anomaly detection in wireless sensor networks. In 2007 IEEE International Conference on Communications, pages 3864–3869, 2007. IEEE.

  19. V. Bhuse and A. Gupta, Anomaly intrusion detection in wireless sensor networks, Journal of High Speed Networks, Vol. 15, No. 1, pp. 33–51, 2006.

    Google Scholar 

  20. M. Tiwari, K. V. Arya, R. Choudhari and K. S. Choudhary, Designing intrusion detection to detect black hole and selective forwarding attack in WSN based on local information. In Fourth International Conference on Computer Sciences and Convergence Information Technology, pages 824–828, Nov 2009. IEEE.

  21. I. Krontiris, T. Dimitriou and F. C. Freiling, Towards intrusion detection in wireless sensor networks. In proceedings of the 13th European Wireless Conference, 2007.

  22. A. P. R. da Silva, M. H. T. Martins, B. P. S. Rocha, A. A. F. Loureiro, L. B. Ruiz and H. C. Wong, Decentralized intrusion detection in wireless sensor networks. In Proceedings of the 1st ACM International Workshop on Quality of Service & Security in Wireless and Mobile Networks, pages 16–23, 2005. ACM.

  23. I. Krontiris, T. Dimitriou, T. Giannetsos and M. Mpasoukos, Intrusion Detection of Sinkhole Attacks in Wireless Sensor Networks, SpringerBerlin, 2008. pp. 150–161.

    Google Scholar 

  24. E. Shakshuki, Y. Maleh, A. Ezzati, Y. Qasmaoui and M. Mbida, A global hybrid intrusion detection system for wireless sensor networks, Procedia Computer Science, Vol. 52, pp. 1047–1052, 2015.

    Article  Google Scholar 

  25. K. Q. Yan, S. C. Wang, S. S. Wang and C. W. Liu, Hybrid intrusion detection system for enhancing the security of a cluster-based wireless sensor network. In 3rd IEEE International Conference on Computer Science and Information Technology, vol. 1, pages 114–118, 2010. IEEE.

  26. A. Agah, S. K. Das, K. Basu and M. Asadi, Intrusion detection in sensor networks: a non-cooperative game approach. In Proceedings of Third IEEE International Symposium on Network Computing and Applications, pages 343–346, 2004. IEEE.

  27. A. Agah and S. K. Das, Preventing DoS attacks in wireless sensor networks: a repeated game theory approach, International Journal of Network Security, Vol. 5, No. 2, pp. 145–153, 2007.

    Google Scholar 

  28. M. Estiri and A. Khademzadeh, A game-theoretical model for intrusion detection in wireless sensor networks. In 23rd Canadian Conference on Electrical and Computer Engineering, pages 1–5, 2010. IEEE.

  29. Y. Qiu, Z. Chen and L. Xu, Active defense model of wireless sensor networks based on evolutionary game theory. In 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM), pages 1–4, 2010. IEEE.

  30. O. A. Wahab, H. Otrok and A. Mourad, A dempster-shafer based tit-for-tat strategy to regulate the cooperation in vanet using qos-olsr protocol, Wireless Personal Communications, Vol. 75, No. 3, pp. 1635–1667, 2014.

    Article  Google Scholar 

  31. G. Shafer, A Mathematical Theory of Evidence, Princeton University PressPrinceton, NJ, 1976.

    MATH  Google Scholar 

  32. B. Subba, S. Biswas and S. Karmakar, Intrusion detection in mobile ad-hoc networks: Bayesian game formulation, Engineering Science and Technology, an International Journal, Vol. 19, No. 2, pp. 782–799, 2016.

    Article  Google Scholar 

  33. O. Abdel Wahab, J. Bentahar, H. Otrok and A. Mourad, Optimal load distribution for the detection of VM-based DDoS attacks in the cloud, IEEE Transactions on Services Computing, Vol. PP, No. 99, pp. 1–1, 2017.

    Article  Google Scholar 

  34. A. Abduvaliyev, S. Lee and Y. K. Lee, Energy efficient hybrid intrusion detection system for wireless sensor networks. In International Conference On Electronics and Information Engineering, vol. 2, pages 25–29, 2010. IEEE.

  35. M. F. H. Sedjelmaci, S. M. Senouci, Intrusion detection framework of cluster-based wireless sensor network. In IEEE Symposium on Computers and Communications, pages 893–897, 2012. IEEE.

  36. N. Nisan, T. Roughgarden, E. Tardos and V. V. Vazirani, Algorithmic Game Theory, Cambridge University PressCambridge, 2007.

    Book  Google Scholar 

  37. X. Deng and C. H. Papadimitriou, On the complexity of cooperative solution concepts, Mathematics of Operations Research, Vol. 19, No. 2, pp. 257–266, 1994.

    Article  MathSciNet  Google Scholar 

  38. S. S. Fatima, M. Wooldridge and N. R. Jennings, A linear approximation method for the shapley value, Artificial Intelligence, Vol. 172, No. 14, pp. 1673–1699, 2008.

    Article  MathSciNet  Google Scholar 

  39. K. V. Aadithya, B. Ravindran, T. P. Michalak and N. R. Jennings, Efficient Computation of the Shapley Value for Centrality in Networks, SpringerBerlin, 2010. pp. 1–13.

    Google Scholar 

  40. N. Megiddo, Computational complexity of the game theory approach to cost allocation for a tree, Mathematics of Operations Research, Vol. 3, No. 3, pp. 189–196, 1978.

    Article  MathSciNet  Google Scholar 

  41. G. F. Riley and T. R. Henderson, The ns-3 network simulator modeling and tools for network simulation. In Modeling and Tools for Network Simulation, pages 15–34, 2010.

    Chapter  Google Scholar 

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Authors and Affiliations

  1. Department of CSE, Indian Institute of Technology Guwahati (IITG), Guwahati, India

    Basant Subba, Santosh Biswas & Sushanta Karmakar

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  1. Basant Subba
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  2. Santosh Biswas
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  3. Sushanta Karmakar
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Correspondence to Santosh Biswas.

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Subba, B., Biswas, S. & Karmakar, S. A Game Theory Based Multi Layered Intrusion Detection Framework for Wireless Sensor Networks. Int J Wireless Inf Networks 25, 399–421 (2018). https://doi.org/10.1007/s10776-018-0403-6

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  • DOI: https://doi.org/10.1007/s10776-018-0403-6

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