Optimal network defense strategy selection based on Bayesian game

被引:0
|
作者
Wang Z.-G. [1 ]
Lu Y. [1 ]
Li X. [1 ]
机构
[1] Shijiazhuang Campus of Army Engineering University, Shijiazhuang
基金
中国国家自然科学基金;
关键词
Attack-defence payoffs; Bayesian game; Defence effectiveness; Incomplete information; Nash equilibrium; Network attack-defence process; Network security; Optimal defence strategy; Pure strategy; Strategy selection;
D O I
10.1504/IJSN.2020.106830
中图分类号
学科分类号
摘要
Existing passive defence methods cannot effectively guarantee network security; to solve this problem, a novel method is proposed that selects the optimal defence strategy. The network attack-defence process is modelled based on the Bayesian game. The payoff is quantified from the impact value of the attack-defence actions. The optimal defence strategy is selected that takes defence effectiveness as the criterion. The rationality and feasibility of the method are verified through a representative example, and the general rules of network defence are summarised. Compared to the classic strategy selection methods based on game theory, the proposed method can select the optimal strategy in the form of pure strategy by quantifying defence effectiveness, which was proven to perform better. Copyright © 2020 Inderscience Enterprises Ltd.
引用
收藏
页码:67 / 77
页数:10
相关论文
共 50 条
  • [31] Optimal attack strategy selection of an autonomous cyber-physical micro-grid based on attack-defense game model
    Ji, Xiao-Peng
    Tian, Wen
    Liu, Weiwei
    Liu, Guangjie
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 12 (09) : 8859 - 8866
  • [32] Optimal attack strategy selection of an autonomous cyber-physical micro-grid based on attack-defense game model
    Xiao-Peng Ji
    Wen Tian
    Weiwei Liu
    Guangjie Liu
    Journal of Ambient Intelligence and Humanized Computing, 2021, 12 : 8859 - 8866
  • [33] A Novel Attack-and-Defense Signaling Game for Optimal Deceptive Defense Strategy Choice
    Hu, Yongjin
    Zhang, Han
    Guo, Yuanbo
    Li, Tao
    Ma, Jun
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2020, 2020
  • [34] Wireless sensor network security defense strategy based on Bayesian reputation evaluation model
    Teng, Zhijun
    Zhu, Sian
    Li, Mingzhe
    Yu, Libo
    Gu, Jinliang
    Guo, Liwen
    IET COMMUNICATIONS, 2024, 18 (01) : 55 - 62
  • [35] Optimal Defense Strategy Selection Algorithm Based on Reinforcement Learning and Opposition-Based Learning
    Yue, Yiqun
    Zhou, Yang
    Xu, Lijuan
    Zhao, Dawei
    APPLIED SCIENCES-BASEL, 2022, 12 (19):
  • [36] Optimal preventive strike strategy vs. optimal attack strategy in a defense-attack game
    Wu, Di
    Yan, Xiangbin
    Peng, Rui
    Wu, Shaoming
    Gao, Kaiye
    2019 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-QINGDAO), 2019,
  • [37] Hybrid game theoretic strategy for optimal relay selection in energy harvesting cognitive radio network
    Bakshi, Shalley
    Sharma, Surbhi
    Khanna, Rajesh
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2024, 37 (17)
  • [38] Markov Evolutionary Games for Network Defense Strategy Selection
    Huang, Jianming
    Zhang, Hengwei
    Wang, Jindong
    IEEE ACCESS, 2017, 5 : 19505 - 19516
  • [39] Optimal Dissemination Strategy of Security Patch Based on Differential Game in Social Network
    Miao, Li
    Li, Shuai
    Wang, Zhongqin
    WIRELESS PERSONAL COMMUNICATIONS, 2018, 98 (01) : 237 - 249
  • [40] Optimal Dissemination Strategy of Security Patch Based on Differential Game in Social Network
    Li Miao
    Shuai Li
    Zhongqin Wang
    Wireless Personal Communications, 2018, 98 : 237 - 249