Optimal attack assignment on remote state estimation in multi nonlinear systems: Structural and asymptotic policy
Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference
Attack, Cyber-physical systems, Extended Kalman Filter, Markov decision process, Remote estimation center, State estimation, Structural results
In this paper, the optimal cyber-attack on remote estimation center in multi nonlinear systems is obtained to study defense strategies in future better. It is assumed that there are independent nonlinear systems, and each of them has a remote sensor for monitoring. An attacker in the network is considered to exacerbate the specific number of communication channels by generating noise. Because of the capacity limitations in real-world systems, a considered attacker can aggravate at most of the communication channels based on its responsibility. The problem is derived as a Markov decision process (MDP) one. Besides, the proof of the existence of an optimal cyber-attack, it is shown that based on the obtained threshold structure of the optimal policy, this problem can be solved for homogeneous models asymptotically, which eases the complexity of computations in real-world applications. In order to check the optimal policy’s performance, numerical results are illustrated.
Zaman, Amirreza; Zarei, Jafar; Razavi-Far, Roozbeh; and Saif, Mehrdad. (2020). Optimal attack assignment on remote state estimation in multi nonlinear systems: Structural and asymptotic policy. Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, 2003-2010.