具有随机丢失的受控状态估计系统的秘密攻击与保密性
Stealthy hacking and secrecy of controlled state estimation systems with random dropouts
摘要：
我们研究的最大信息增益，对手可以通过黑客攻击而不被发现。考虑由传感器观察到的动态过程，该传感器根据一些参考传输策略跨配备有应答（ACK）的分组丢弃无线信道将系统状态的本地估计传输到远程估计器。对手偷听到传输并主动劫持传感器以重新编程其传输策略。我们定义完美的秘密保持平均期望误差协方差有界的合法估计和无界的对手。通过分析期望误差协方差的平稳分布，我们表明，完美的秘密可以达到不稳定的系统，只有当ACK信道没有数据包丢失。在其他情况下，我们证明了独立的参考政策和检测方法，完美的保密是无法实现的。对于这种情况下，我们制定了一个受约束的马尔可夫决策过程，以获得最佳的传输策略，对手应该在传感器上实现，并设计了一个Stackelberg游戏，以获得最佳的参考策略的合法估计。
英文摘要：
We study the maximum information gain that an adversary may obtain through hacking without being detected. Consider a dynamical process observed by a sensor that transmits a local estimate of the system state to a remote estimator according to some reference transmission policy across a packet-dropping wireless channel equipped with acknowledgments (ACK). An adversary overhears the transmissions and proactively hijacks the sensor to reprogram its transmission policy. We define perfect secrecy as keeping the averaged expected error covariance bounded at the legitimate estimator and unbounded at the adversary. By analyzing the stationary distribution of the expected error covariance, we show that perfect secrecy can be attained for unstable systems only if the ACK channel has no packet dropouts. In other situations, we prove that independent of the reference policy and the detection methods, perfect secrecy is not attainable. For this scenario, we formulate a constrained Markov decision process to derive the optimal transmission policy that the adversary should implement at the sensor, and devise a Stackelberg game to derive the optimal reference policy for the legitimate estimator.
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