Optimal Attack Energy Allocation Against Remote Estimation in Cyber-Physical Systems

This brief focuses on designing an optimal attack energy allocation strategy to disrupt the performance of remote state estimation with unknown gains for cyber-physical systems (CPSs). To deal with the unknown gains, the Cramér-Rao Bound (CRB) is introduced to obtain a lower bound of the secondary moment of the estimate error. Then, by solving an optimization problem that maximizes the average CRB over a finite time horizon with energy constraint, an optimal attack energy allocation strategy is derived. Compared with the existing works, the rigorous assumption that the attacker has full knowledge of the system is removed, and the computational complexity of solving the optimization problem is significantly reduced. Finally, numerical results validate the presented strategy.