Remote State Estimation Against Essential-Information-Aware Attack Tactic in Cyber-Physical Systems
Haotong Lv, Chao Cheng, Yiyang Chen, Engang Tian · IEEE Transactions on Automation Science and Engineering · 2025
From the perspective of attackers, this article proposes a creative essential-information-aware (EIA) attack policy targeting remote state estimation in cyber-physical systems (CPSs), in which adversaries aim at maximizing the trace of estimation error covariance by selectively leveraging crucial information during data transmission. Through manipulating the transmitted signals, the attacker can recognize critical packets exchanged among sensing nodes and allocate higher attack energy level to them, thereby enlarging the attack success probability (ASP) and amplifying the disruptive effect. Then, a scientific power allocation scenario has been designed with the aid of signal-to-interference-plus-noise ratio (SINR), while explicitly accounting for the confinement imposed by limited channel transmission capacity. Furthermore, the relationships among the attack coefficient, ASP, attack cost, and the channel capacity are rigorously analyzed utilizing stochastic methods. The upper bounds for attack coefficient are derived to balance attack impact with resource limitations. Finally, two examples are provided to verify the effectiveness and practicality of the attack strategy.