Optimal Deception Attacks on Remote State Estimation with Heterogeneous Vulnerabilities

This study explores optimal deception attacks on remote state estimation, focusing on scenarios with heterogeneous vulnerabilities. Acknowledging the limitations of attackers’ resources and defenders’ capabilities, it is usually infeasible to attack all transmission channels. Additionally, a channel might not simultaneously be vulnerable to both eavesdropping and tampering, since the requirements and implementations are different between these two activities. Therefore, “heterogeneous vulnerabilities” are introduced to characterize various degrees of susceptibility to malicious activities in all channels. Within this context, the design of deception attacks is becoming challenging due to more constraints and less information available. To maintain stealthiness strictly and disrupt estimators maximally, an attack model is constructed through the efficient integration of available information. Subsequently, the corresponding optimization problem is solved explicitly to determine the optimal coefficients. Finally, numerical simulations are employed to validate the theoretical results.