Synthesis of the Supremal Covert Attacker Against Unknown Supervisors by Using Observations

• 成果类型: Article
• 署名作者: Tai, Ruochen; Lin, Liyong; Zhu, Yuting; Su, Rong
• 署名单位: Nanyang Technological University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3191393
• 发表日期: 2023
• 页码: 3453-3468
• 关键词: Closed loop systems; actuators; Automata; Adaptation models; STANDARDS; security; Discrete-event systems; cyber-physical system; covert attack; discrete-event system; learning; partial-observation; supervisor synthesis; supremality; unknown model

摘要

In this article, we consider the problem of synthesizing the supremal covert damage-reachable attacker, in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system. The synthesized attacker needs to ensure both the damage-reachability and the covertness against all the supervisors, which are consistent with the given set of observations. There is a gap between the de facto supremality, assuming the model of the supervisor is known, and the supremality that can be attained with a limited knowledge of the model of the supervisor, from the adversary's point of view. We consider the setup where the attacker can exercise sensor replacement/deletion attacks and actuator enablement/disablement attacks. The solution methodology proposed in this article is to reduce the synthesis of the supremal covert damage-reachable attacker, given the model of the plant and the finite set of observations, to the synthesis of the supremal safe supervisor for certain transformed plant, which shows the decidability of the observation-assisted covert attacker synthesis problem. The effectiveness of our approach is illustrated on a water tank example adapted from the literature.