Optimal strategy of data tampering attacks for FIR system identification with average entropy and binary-valued observations

In the era of digitalization boom, cyber-physical system (CPS) has been widely used in several fields. However, malicious data tampering in communication networks may lead to degradation of the state estimation performance, which may affect the control decision and cause significant losses. In this paper, for the identification of finite impluse response (FIR) systems with binary-valued observations under data tampering attack, an optimal attack strategy based on the average entropy is designed from the perspective of the attacker. In the case of unknown parameters, the regression matrix is used to give the estimation method of the system parameters, the algorithmic flow of the data tampering attack for the implementation of the on-line attack is designed. Finally, the effectiveness of the algorithm and the reliability of the conclusions is verified through the examples.