Optimal Stealthy Attacks With Historical Data in Cyber-Physical Systems Under Periodic Detection

This article addresses the formulation and design of stealthy attack strategies for cyber-physical systems (CPSs) with mismatched control and detection cycles. A linear attack strategy grounded in historical innovation sequences is formulated, where strict stealthiness is enforced at detection instants and an energy constraint is applied at nondetection instants. By exploiting the intrinsic relationships among stealthiness-related parameters, the originally nonconvex optimization problem is reformulated into one with a single equality constraint, whereby the closed-form optimal attack parameters can be directly derived, and the numerical iterative procedures relied upon in the existing results are avoided. The achieved degradation in state-estimation performance exceeds that of the previously existing strategies. Finally, the numerical simulations are provided to validate the effectiveness and advantages of the proposed approach.