The optimal false data injection attacks based on zonotopes

This paper proposes an attack detection method and an optimal false data injection (FDI) attack strategy based on zonotopic theory. A linear discrete-time system with unknown-but-bounded (UBB) noise is considered, and it is assumed that the attacker can obtain the full knowledge of the system. Based on the estimation residue, a novel attack detection method is proposed. In addition, the conditions that an attacker needs to satisfy are given, which can guarantee that attacks are stealthy. Finally, a simulation example is provided to illustrate the effectiveness of the main results.