XIA Jinzong1, DU Yongwen1, L Xiaojian2, MA Ji1
（1. School of Electronics & Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China；2. China Shipbuilding Industry Corporation No.722 Institute, Wuhan 430000, China）
Abstract： When using traditional game methods to study information security of the wireless sensor networks, players are mostly based on the assumption of completely rational. Based on bounded rationality, the evolutionary game theory is used to establish the attack-defense model, analyze the strategy selection process of players, solve the evolutionarily stable strategy and design the optimal strategy selection algorithm. Then, considering the strategy dependence, the incentive and punishment mechanism is introduced to improve the replicator dynamic equation. The simulation results show that the model is reasonable and the algorithm is effective, which provides new theoretical support for the security of wireless sensor networks.
Key words： wireless sensor networks (WSNs)； evolutionary game； replicators dynamic equation
References
［1］QIANZ, WANG Y. Overview of wireless sensor networks facing the Internet of things. Journal of Electronics and Information Technology, 2013, 35(1)： 215-227.
［2］SERRA E, JAJODIA S, PUGLIESE A, et al. Pareto-optimal adversarial defense of enterprisesystems. ACM Transaction on Information & System Security, 2015, 17(3)： 1-39.
［3］RICHARD L, JOSHUA W. Analysis and results of he DARPA off-line intrusion detection evaluation//17th International Workshop on Recent Advances in Intrusion Detection. Beijing: Springer, 2014： 162-182.
［4］XU X. Research on wireless sensor network intrusion detection based on game.Wuhan： Huazhong University of Science and Technology, 2016.
［5］PEI Q, SHEN Y, MA J. Overview of wireless sensor network security technology. Journal of Communications, 2007(8)： 113-122.
［6］CONITZER V, SANDHOLM T. Computing the optimal strategy to commit to//The 7th ACM Conference on Electronic Commerce, Jun. 11, 2006, Ann Arbor, Michigan, USA, New York： Association for Computing Machinery, 2006： 82-90.
［7］PARUCHURI P, PEARCE J P. Playing games for security： an effiffifficient exact algorithm for solving bayesian stackelberg games//The 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’08), May 12-16, 2008, Estoril, Portugal, RichlandSC： International Foundation for Autonomous Agents and Multiagent Systems, 2008： 895-902.
［8］WANG Z, YUAN Y, AN B, et al. Research review of security game theory. Journal of Command and Control, 2015, 1(2)： 121-149.
［9］OCEVICIC H, NENADIC K, SOLIC K. Game theory： active defense model and method. IEEE Information and Network Security, 2016, 51(8)： 395-406.
［10］GHOSH D, SHARMA A, SHUKLA K K, et al. Globalized robust Markov perfect equilibrium for discounted stochastic games and its application on intrusion detection in wireless sensor networks： Part I-theory. Japan Journal of Industrial and Applied Mathematics, 2020, 37(1)： 283-308.
［11］SHEN S. Game theory and wireless sensor network security. Beijing： Tsinghua University Press, 2015.
［12］LYE K W, WING J. Game strategies in network security. International Journal of Information Security, 2005, 4(1/2)： 71-86.
［13］LIN W, WANG H, LIU J. Research on active defense technology of network security based on non-cooperative dynamic game. Journal of Computer Research and Development, 2013, 48(2)： 306-316.
［14］GUI M, LIU Y, ZHOU Q. Research on intrusion detection based on game theory in WSN. Journal of Chongqing University of Posts and Telecommunications (natural science edition), 2016, 28(3)： 414-420.
［15］HAN L, ZHOU M, JIA W,et al. Intrusion detection model of wireless sensor networks based on game theory and an auto regressive model. Information Sciences, 2019, 476： 491-504.
［16］SUN Q, LU L, YAN G, et al. Stability analysis of evolutionary game equilibrium under incomplete information. Systems Engineering Theory and Practice, 2003(7)： 11-16.
［17］WANG W. Current situation and prospect of evolutionary game theory research. Statistics and Decision-making, 2009(3)： 158-161.
［18］SUN W. Research on information security attack and defense based on evolutionary game theory. Information Science, 2015(9)： 1408-1412.
［19］GAN W, CHEN Z Y, WANG Q. Selection of optimal defense strategies for the Internet of things based on evolutionary game. Weapons Equipment Engineering, 2019, 41(1)： 130-135.
［20］HUANG J, ZHANG H, WANG J, et al. Selection method of defense strategies based on the evolutionary game model of offense and defense. Journal of Communications, 2017, 38(1)： 168-176.
一种基于演化博弈的无线传感器网络安全决策算法
夏金棕1， 杜永文1， 吕晓剑2， 马吉1
（1. 兰州交通大学 电子与信息工程学院， 甘肃 兰州 730070；2. 中国船舶重工集团公司第七二二研究所， 湖北 武汉 430000）
摘要:研究无线传感器网络（wireless sensor networks， WSNs)安全时， 针对恶意入侵攻击， 传统博弈大多是基于参与者完全理性提出假设。 本文首先针对现实社会中的有限理性条件， 运用演化博弈理论建立攻防模型， 分析博弈双方的策略选择过程， 求解演化稳定均衡并设计最优策略选取算法。 其次考虑到攻防过程的策略依存性， 引入奖励惩罚机制改进复制者动态方程， 探究奖惩因子对攻防双方策略收敛的影响。 仿真结果表明该模型的合理性和算法的有效性， 该方案可为无线传感器网络安全机制设计提供参考。
关键词:无线传感器网络(WSNs)； 演化博弈； 复制动态方程
引用格式：XIA Jinzong, DU Yongwen, L Xiaojian, et al. An evolutionary game based security decision algorithm for wireless sensor networks. Journal of Measurement Science and Instrumentation， 2022， 13（4）：460-470. DOI： 10.3969／j.issn.1674-8042.2022.04.009
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