On Attack Mitigation in Supervisory Control Systems: A Tolerant Control Approach
Jingshi Yao, Xiang Yin, Shaoyuan Li · 2020
This paper investigates attack mitigation problem in supervisory control of discrete event systems. We consider the scenario where the system is subject to actuator enablement attack. We explicitly distinguish between controllable events and defendable events; the former are events that can be disabled by the normal supervisor but may be subject to attack, while the latter are events that can be defensed (disabled definitely) by the mitigation module but possibly with higher costs. The objective is to design an attack mitigation strategy to prevent serious damage from attack. We formulate the attack mitigation problem as a tolerant control problem under partial observation. Particularly, in addition to guarantee safety, we aim to maximize the desirable behavior (normal specification) while minimize the tolerable behavior (safe but not desirable). We provide an effective online algorithm for solving this problem, which yields a novel attack mitigation strategy that generalizes the existing one in the literature. Specifically, we show that the proposed strategy may still prevent damage even when the safe-controllability condition, which is required by the existing strategy, does not hold.