A Secure Encoding Mechanism Against Deception Attacks on Multisensor Remote State Estimation

This paper studies the defense strategy of remote state estimation under deception attacks. In order to prevent the stealthy attacker from reducing the estimation performance without triggering an alarm, an encoding-decoding mechanism combining linear transformation and artificial noise is proposed. Moreover, the detection performance under three different attack scenarios is analyzed. It is proved that the false data detector can effectively identify the attack or weaken its impact on the system under the proposed strategy, so as to ensure the security of the system. From the perspective of an attacker, an algorithm that can deduce the approximate values of the encoding parameters is also provided, which reveals how the magnitude of the artificial noise affects the accuracy of the attacker’s inference. Finally, a simulation example is presented to verify the effectiveness of the developed approach.