一个贝叶斯斯斯塔克尔伯格游戏方法,在基于SINR的DoS攻击下进行远程状态估计,信息不完整
Di Deng1,2, Peng Yi1,2, Mingze Qi3,4
1Department of Control Science and Engineering, Tongji University, Shanghai 201804, China.
Sensors (Basel, Switzerland)
|February 27, 2026
概括
这项研究引入了贝叶斯斯斯塔克尔伯格游戏,以优化传感器传输和攻击者干扰策略,以应对拒绝服务 (DoS) 攻击,增强在能源限制下远程状态估计.
科学领域:
- 网络物理安全 网络物理安全
- 游戏理论 游戏理论
- 信息理论 信息理论
背景情况:
- 拒绝服务 (DoS) 攻击对网络物理系统构成重大威胁,特别是影响远程状态估计.
- 由于能源有限,传感器需要有效的传输和干扰策略.
- 关于攻击者道获取的不完整信息使防御机制复杂化.
研究的目的:
- 在基于信号与干扰加噪声比 (SINR) 的DoS攻击下,调查Stackelberg对传感器和攻击者在远程状态估计中的游戏策略.
- 开发一种平衡传感器估计性能和能源消耗的方法.
- 为了解决关于攻击者的通道收益的不完整信息的场景.
主要方法:
- 制定日程安排问题作为一个马尔科夫决策过程在无限的时间地平线.
- 构建一个贝叶斯斯斯塔克尔伯格游戏 (BSG),结合概率通道获取信息.
- 应用最佳响应定义来解决BSG并证明斯塔克尔贝格平衡的存在.
- 利用Stackelberg的Q学习算法来为传感器和攻击者得出最佳策略.
主要成果:
- 提出的贝叶斯斯斯塔克尔伯格游戏有效地模拟了传感器和攻击者之间的战略互动.
- 斯塔克尔伯格的Q学习算法成功地确定了最佳的传输和干扰策略.
- 数字结果验证了游戏方法的有效性,即使传感器缺乏对攻击者的通道收益的精确知识.
结论:
- 开发的游戏理论方法提供了一个有效的框架,可以在能源限制和不完整信息下防御DoS攻击的远程状态估计.
- 这些发现强调了适应性策略在网络物理安全方面的重要性.
- 该研究表明,在敌对环境中增强系统弹性是一种可行的解决方案.
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