Stochastic Detector against linear deception attacks on remote state estimation

In this paper, an attack detection problem in cyber-physical systems is studied. In a scenario of remote state estimation, the measurement innovation sent by a sensor through a wireless communication channel may be modified by a malicious attacker deceptively. To avoid using an approximate minimum mean squared error (MMSE) estimator introduced by the traditional χ2 detector with a fixed threshold, and inspired by the ideas of event-based sensor schedules, we propose a stochastic detector with a random threshold for the remote estimator to determine whether to fuse the received data or not. The corresponding effect of the proposed detector on the estimation performance under linear deception attacks is analyzed explicitly. Simulations are provided to illustrate the developed results.

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