Improving the security of wireless sensor networks using Game Theory

Subject Areas : Network Security

Behzad Seif ¹ (Department of Computer Engineering, Garmsar branch, Islamic Azad University, Garmsar, IRAN)
mohammad goodarzi ² (Mohammad goodarzi ,Computer Engineering Department, Islamic Azad University Garmsar branch, IRAN ([e-mail]).)

Received: 2021-02-22 Accepted : 2021-10-09 Published : 2021-05-01

Keywords: Game theory, Sleep Prevention Attack, wireless sensor networks, Authentication,

Abstract :

Today, the use of wireless sensor networks has become very popular in many applications. Due to the connection in wireless sensor networks, it is done wirelessly, so they are naturally insecure and prone to various types of attacks. In the past, various solutions were offered in this regard, each of which had its problems. Therefore, in this proposed solution, an attempt was made to solve these problems. The proposed solution for securing sensor nodes uses authentication based on the ZKP protocol, which has been improved with Interlock, and game theory has also been used to more quickly identify intrusive nodes. One of the most important benefits of the proposed solution is to prevent attacks such as sleep deprivation. The proposed algorithm is able to detect quickly and is able to prevent network damage in the fastest possible time. The proposed solution was implemented and reviewed in MATLAB environment and the studies showed a very good performance of the proposed method.

References:

[1]    K. Sharma and S. Pradhan, "Cluster Head Rotation in Wireless Sensor Network: A Simplified Approach," International Journal of Sensor and Its Applications for Control Systems, vol. 4, no. 1, pp. 1-10, 2016. 
[2]    S.-H. Seo, J. Won and S. Sultana, "Effective Key Management in Dynamic Wireless Sensor Networks," IEEE Transactions on Information Forensics and Security, vol. 10, no. 2, pp. 371-383, 2015. 
[3]    A. Abbasi and Y. M, "A survey on clustering Algorithms for Wireless Sensor Networks," Computer Communications, vol. 30, pp. 2826-2841, 2007. 
[4]    "Energy efficient homogenous clustering algorithm for wireless," Internations journals of Wireless Sensor Network, vol. 2, pp. 49-61, 2010. 
[5]    F. Akyildiz and M. lan, Wireless Sensor Network, Wiley, 2010. 
[6]    A. Laszka, M. Felegyhazi, L. Buttyan, "A Survey of Interdependent Information Security Games," ACM Computing Surveys, vol. 47, no. 2, 2015. 
[7]    W. Saad, T. Alpcan, T. Basar and A. Hjorungnes, "Coalitional Game Theory for Security Risk Management," Fifth International Conference on Internet Monitoring and Protection, pp. 35-40, 2010. 
[8]    J. Grossklags, N. Christin and J. Chuang, "Secure or insure?: a game-theoretic analysis of information security games," Proceedings of the 17th international conference on World Wide Web, pp. 209-218, 2008. 
[9]    Y. E. Sagduyu, R. A. Berry and A. Ephremides, "Jamming games in wireless networks with incomplete information," IEEE Communications Magazine, vol. 49, no. 8, pp. 112-118, 2011. 
[10]    M. Fallah, "A Puzzle-Based Defense Strategy Against Flooding Attacks Using Game Theory," IEEE Transactions on Dependable and Secure Computing, vol. 7, no. 1, pp. 5-19, 2010. 
[11]    L. Chen and J. Leneutre, "A Game Theoretical Framework on Intrusion Detection in Heterogeneous Networks," IEEE Transactions on Information Forensics and Security, vol. 4, no. 2, pp. 165-178, 2009. 
[12]    M. H. Manshaei, Q. Zhu, T. Alpcan, T. Bacşar, J.-P. Hubaux, "Game theory meets network security and privacy," ACM Computing Surveys, vol. 45, no. 3, 2013. 
[13]    Z. Zhou and Z. Sun, "A Lightweight and Dependable Trust Model for Clustered Wireless Sensor Networks," Cloud Computing and Security, vol. 9483, pp. 157-168, 2015. 
[14]    G. Dogan and K. Avincan, "MultiProTru: A kalman filtering based trust architecture for two-hop wireless sensor networks," Peer-to-Peer Networking and Applications, pp. 1-14, 2016. 
[15]    D. Fang, L. Gao, Z. Tang and X. Chen, "A Software Protection Framework Based on thin virtual machine using distorted encryption," 2011. 
[16]    P. Bommannavar, T. Alpcan and N. Bambos, "Security Risk Management via Dynamic Games with Learning," IEEE International Conference on Communications, pp. 1-6, 2011. 
[17]    S. Mirjalili, L. A. Mirjalili, "The whale optimization algorithm," Advances in Engineering Software, vol. 95, pp. 51-67, 2016. 
[18]    D. R. R. a. S. F. M. Bradley, "Clustered Adaptive Rate Limiting: Defeating Denial-Of-Sleep Attacks In Wireless Sensor Networks," IEEE, 2017. 
[19]    V. Tiri, M. Night, T. axis, S. Parbat, "Zero knowledge protocol to design security model for threats in WSN," Int. J. Eng. Res. Appl.(IJERA), vol. 2, pp. 1533-1537, 2012. 
[20]    R. Sangeetha, Y. M. Sangeetha, "Secure energy-aware multipath routing protocol with transmission range adjustment for wireless sensor networks," In Computational Intelligence & Computing Research (ICCIC), pp. 1-4, 2018.
[21]    Y. ZHANG, C. WU, J. CAO, X. LI: A secret sharing-based key management in hierarchical wireless sensor network, International Journal of Distributed Sensor Networks, 9(6), 406061, 2013.
[22]    S. RANJEETHA, N. RENUGA, R. SHARMILA: Secure zone routing protocol for MANET, International Conference on Emerging Trends in Engineering, Science and Sustainable Technology, (ICETSST), 67-76, 2017.
[23]    T. YANG, X. XIANGYANG, L. PENG, L. TONGHUI: A secure routing of wireless sensor networks based on trust evaluation model, Procedia Computer Science, 131 (2018), 1156- 1163.
[24]    A. T. ALGHAMDI: Convolutional technique for enhancing security in wireless sensor networks against malicious nodes, Human-centric Computing and Information Sciences, 9(1), ID38, https://doi.org/10.1186/s13673-019-0198-1, 2019.