Random-Enabled Hidden Moving Target Defense against False Data Injection Alert Attackers

Hidden moving target defense (HMTD) is a proactive strategy that kept hidden from attackers by changing the reactance of transmission lines to thwart false data injection (FDI) attacks. However, alert with strong capabilities pose additional risks HMTD and thus, it much-needed evaluate hiddenness HMTD. This paper first summarizes two existing attacker models, i.e., bad-data-detection-based data-driven attackers. Furthermore, this proposes novel model-based model uses MTD operation models estimate dispatched line reactance. The proposed can use estimated construct stealthy FDI attacks against methods lack randomness. We propose random-enabled (RHMTD) method, which utilizes random weights introduce randomness derived conditions as constraints. RHMTD theoretically proven be three models. In addition, we analyze detection effectiveness Simulation results on IEEE 14-bus systems show traditional fail detect attacker, effective in detecting