Optimal Attack Energy Allocation against Remote State Estimation

Recently, the security issue of wireless cyber-physical systems (CPS) has attracted much attention from different communities. In this paper, we consider energy-efficient optimal attack power schedule against remote state estimation of wireless CPS under constrained denial-of-service attacks based on channels' signal-to-interference-plus-noise ratio (SINR). We propose a wireless communication model with SINRs of channels, in which different attack powers can cause different dropout rates. The problem of optimal attack power schedule that causes the largest performance degradation of the remote state estimation, subject to attacker's average energy constraint in multisystems, is solved by formulating it as a Markov decision process. We show that an optimal deterministic and stationary policy exists and the optimal policy has a threshold structure.