Remote State Estimation in the Presence of an Active Eavesdropper

We consider remote state estimation in the presence of an active eavesdropper. A sensor forward local estimates to a estimator over network, which may be eavesdropped by intelligent adversary. Aiming at improving eavesdropping performance efficiently, adversary adaptively alternate between and mode. In contrast eavesdropping, attack enables sabotage data transfer estimator, improve reception itself same time. However, launching attacks increase risk being detected. As result, tradeoff stealthiness arises. present generalized framework for propose criterion based on packet rate evaluate Moreover, is formulated as constrained Markov decision process. After deriving sufficient condition under least one stationary policy satisfies constraint also bounds performance, we develop optimal eavesdropper focus structural analysis policy. Furthermore, numerical examples are provided illustrate developed results.