Innovation‐Based Tampering Attack on Remote State Estimation With Quantized Observations

As cyber‐physical systems become increasingly prevalent in industries, their network data transmissions are subject to growing security threats. When the current attack detection mechanism is introduced at the sensor side, this article proposes a stochastic tampering attack strategy on quantized state estimation using feedback information and innovations. The attack not only deceives the detector, avoiding the identification of the attack strategy by the defender, but also greatly weakens the state estimation performance. Meanwhile, the corresponding state estimation equations are presented from the adversary's perspective, and further analysis is conducted on the impact of the attack on estimation accuracy. Then, from the attacker's view, we design the optimal attack strategy to maximize the estimation error, and further analyze the convergence of the error metrics under different attack strategies. Finally, theoretical results are verified by simulation examples.