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WSNs多阶段入侵检测博弈最优策略研究

周伟伟 郁滨

周伟伟, 郁滨. WSNs多阶段入侵检测博弈最优策略研究[J]. 电子与信息学报, 2018, 40(1): 63-71. doi: 10.11999/JEIT170323
引用本文: 周伟伟, 郁滨. WSNs多阶段入侵检测博弈最优策略研究[J]. 电子与信息学报, 2018, 40(1): 63-71. doi: 10.11999/JEIT170323
ZHOU Weiwei, YU Bin. Optimal Defense Strategy in WSNs Based on the Game of Multi-stage Intrusion Detection[J]. Journal of Electronics & Information Technology, 2018, 40(1): 63-71. doi: 10.11999/JEIT170323
Citation: ZHOU Weiwei, YU Bin. Optimal Defense Strategy in WSNs Based on the Game of Multi-stage Intrusion Detection[J]. Journal of Electronics & Information Technology, 2018, 40(1): 63-71. doi: 10.11999/JEIT170323

WSNs多阶段入侵检测博弈最优策略研究

doi: 10.11999/JEIT170323
基金项目: 

信息保障重点实验室开放基金(KJ-15-104),河南省科技攻关项目(132102210003)

Optimal Defense Strategy in WSNs Based on the Game of Multi-stage Intrusion Detection

Funds: 

The National Science Key Laboratory Fund (KJ-15-104), The Project of Key Scientific and Technological Research of Henan Province (132102210003)

  • 摘要: 针对无线传感器网络中资源受限的入侵检测系统策略优化问题,该文提出一种多阶段动态入侵检测博弈模型。该模型利用贝叶斯规则修正下一阶段外部节点为恶意节点的后验概率,通过分析推导给出最易遭受攻击的节点集合。以建立的模型和节点集合为依据,求解了满足完美贝叶斯均衡条件的入侵检测最优策略。在此基础上,设计了入侵检测最优策略方案。仿真实验结果表明,该方案在提高簇形结构检测防御成功率方面有明显优势。
  • 郁滨, 周伟伟. ZigBee同频攻击检测抑制模型研究[J]. 电子与信息学报, 2015, 37(9): 2211-2217. doi: 10.11999/JEIT 141395.
    YU B and ZHOU W W. Co-channel attack detection and suppression model for ZigBee network nodes[J]. Journal of Electronics Information Technology, 2015, 37(9): 2211-2217. doi: 10.11999/JEIT141395.
    杜晔, 张亚丹, 黎妹红, 等. 基于改进FastICA算法的入侵检测样本数据优化方法[J]. 通信学报, 2016, 37(1): 42-48. doi: 10.11959/j.issn.1000-436x.2016006.
    DU Y, ZHANG Y D, LI M H, et al. Improved Fast ICA algorithm for data optimization processing in intrusion detection[J]. Journal on Communications, 2016, 37(1): 42-48. doi: 10.11959/j.issn.1000-436x.2016006.
    杨安, 孙利民, 王小山, 等. 工业控制系统入侵检测技术综述[J]. 计算机研究与发展, 2016, 53(9): 2039-2054. doi: 10.7544 /issn.1000-1239.2016.20150465.
    YANG A, SUN L M, WANG X S, et al. Intrusion detection techniques for industrial control systems[J]. Journal of Computer Research and Development, 2016, 53(9): 2039-2054. doi: 10.7544/issn.1000-1239.2016.20150465.
    赵婧, 魏彬, 罗鹏, 等. 基于隐马尔可夫模型的入侵检测方法[J]. 四川大学学报, 2016, 16(1): 106-110. doi: 10.15961/ j.jsuese.2016.01.016.
    ZHAO J, WEI B, LUO P, et al. Intrusion detection method based on hidden Markov model[J]. Journal of Sichuan University, 2016, 16(1): 106-110. doi: 10.15961 /j.jsuese.2016. 01.016.
    KOLIAS C, KOLIAS V, and KAMBOURAKIS G. TermID: A distributed swarm intelligence-based approach for wireless intrusion detection[J]. International Journal of Information Security, 2016, 21(6): 1-16. doi: 10.1007/s10207-016-0335-z.
    YU Q, LYU J, JIANG L, et al. Traffic anomaly detection algorithm for wireless sensor networks based on improved exploitation of the GM (1, 1) model[J]. International Journal of Distributed Sensor Networks, 2016, 12(7): 218-227. doi: 10.1177/155014772181256.
    PATEL A, ALHUSSIAN H, PEDERSEN J M, et al. A nifty collaborative intrusion detection and prevention architecture for Smart Grid ecosystems[J]. Computers Security, 2017, 64(2): 92-109. doi: 10.1016/j.cose.2016.07.002.
    KALNOOR G, AGARKHED J, and PATIL S R. Agent- based QoS routing for intrusion detection of sinkhole attack in clustered wireless sensor networks[C]. The First International Conference on Computational Intelligence and Informatics, Hyderabad, India, 2017: 571-583. doi: 10.1007/ 978-981-10-2471-9_55.
    WANG X Y, YANG L Z, and CHEN K F. Sleach: secure low-energy adaptive clustering hierarchy protocol for wireless sensor networks[J]. Wuhan University Journal of Natural Sciences, 2005, 10(1): 127-131. doi: 10.1007/BF02828633.
    FOROOTANINIA A and GHAZNAVI M B. An improved watchdog technique based on power-aware hierarchical design for ids in wireless sensor networks[J]. International Journal of Network Security, 2012, 4(4): 161-178. doi: 10.5121/ijnsa. 2012.4411.
    DOUMIT S S and AGRAWAL D P. Self-organized criticality and stochastic learning based intrusion detection system for wireless sensor networks[C]. Military Communications Conference, Alexandria, USA, 2003: 609-614. doi: 10.1109/ MILCOM.2003.1290173.
    XIAO Z H, CHEN Z G, and DENG X H. Anomaly detection based on a multi-class CUSUM algorithm for WSN[J]. Journal of Computers, 2010, 5(2): 306-313. doi: 10.4304/jcp. 5.2.306-313.
    JOKAR P and LEUNG V. Intrusion detection and prevention for ZigBee-based home area networks in smart grids[J]. IEEE Transaction on Smart Grid, 2016, 15(3): 1-12. doi: 10.1109/TSG.2016.2600585.
    MOOSAVI H and BUI F M. A game-theoretic framework for robust optimal intrusion detection in wireless sensor networks[J]. IEEE Transactions on Information Forensics and Security, 2014, 9(9): 1367-1379. doi: 10.1109/TIFS.2014. 2332816.
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出版历程
  • 收稿日期:  2017-04-13
  • 修回日期:  2017-09-01
  • 刊出日期:  2018-01-19

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