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首页> 外文期刊>Computers, Materials & Continua >Defense Strategies Against Network Attacks in Cyber-Physical Systems with Analysis Cost Constraint Based on Honeypot Game Model
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Defense Strategies Against Network Attacks in Cyber-Physical Systems with Analysis Cost Constraint Based on Honeypot Game Model

机译：基于蜜罐游戏模型的分析成本约束，对网络 - 物理系统网络攻击的防御策略

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摘要

Cyber-physical system (CPS) is an advanced system that integrats physical processes, computation and communication resources. The security of cyber-physical systems has become an active research area in recent years. In this paper, we focus on defensive strategies against network attacks in CPS. We introduce both low- and high-interaction honeypots into CPS as a security management tool deliberately designed to be probed, attacked and compromised. In addition, an analysis resource constraint is introduced for the purpose of optimizing defensive strategies against network attacks in CPS. We study the offensive and defensive interactions of CPS and model the offensive and defensive process as an incomplete information game with the assumption that the defender's analysis resource is unknown to the attacker. We prove the existence of several Bayesian-Nash equilibria in the low- and high-interaction honeypot game without analysis cost constraints and obtain the attacker's equilibrium strategy firstly. Then, we take the impact of analysis cost on the capture effect of honeypots into consideration and further optimize the defensive strategy by allocating analysis resource between low- and high-interaction honeypot with resource constraint. Finally, the proposed method is evaluated through numerical simulation and prove to be effective in obtaining the optimal defensive strategy.
机译：网络物理系统（CPS）是一种高级系统，可整容物理过程，计算和通信资源。近年来，网络物理系统的安全已成为一个活跃的研究区域。在本文中，我们专注于对CPS网络攻击的防御策略。我们将低交互蜜罐介绍为CPS作为刻意探测，攻击和妥协的安全管理工具。此外，介绍了分析资源约束，以优化对CPS中网络攻击的防御策略。我们研究了CPS和模型攻击性和防守过程的攻击性和防御过程，作为一个不完整的信息游戏，假设攻击者对后卫的分析资源未知。我们证明了在低互动蜜罐游戏中的几个贝叶斯 - 纳什均衡的存在，没有分析成本限制，首先获得攻击者的均衡战略。然后，我们考虑了分析成本对蜜罐捕获效果的影响，并通过资源约束分配了低互动蜜罐之间的分析资源来进一步优化防御策略。最后，通过数值模拟来评估所提出的方法，并证明在获得最佳防御策略方面有效。

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  • 来源
    《Computers, Materials & Continua》 |2019年第1期|193-211|共19页
  • 作者

    Wen Tian; Xiaopeng Ji; Weiwei Liu; Guangjie Liu; Rong Lin; Jiangtao Zhai; Yuewei Dai;

  • 作者单位

    School of Automation Nanjing University of Science and Technology Nanjing 210094 China;

    School of Automation Nanjing University of Science and Technology Nanjing 210094 China;

    School of Automation Nanjing University of Science and Technology Nanjing 210094 China;

    School of Automation Nanjing University of Science and Technology Nanjing 210094 China;

    School of Automation Nanjing University of Science and Technology Nanjing 210094 China Department of Engineering Durham University South Road Durham DH1 3LE UK;

    School of Electrics and Information Engineering Jiangsu University of Science and Technology Zhenjiang 212003 China;

    School of Electrics and Information Engineering Jiangsu University of Science and Technology Zhenjiang 212003 China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Honeypot; game theory; cyber-physical system; network attack; human analysis cost;

    机译：蜜罐;博弈论;网络物理系统;网络攻击;人类分析成本;

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