Attack-Resilient Supervisory Control of Discrete-Event Systems: A Finite-State Transducer Approach
It addresses the problem of supervisory control resilience in cyber-physical systems against a general class of sensor/actuator attacks, offering a systematic approach with theoretical guarantees.
This work proposes a finite-state transducer framework to design attack-resilient supervisors for discrete-event systems under regular-rewriting attacks, providing polynomial-complexity algorithms and an open-source tool demonstrated via a case study.
Resilience to sensor and actuator attacks is a major concern in the supervisory control of discrete events in cyber-physical systems (CPS). In this work, we propose a new framework to design supervisors for CPS under attacks using finite-state transducers (FSTs) to model the effects of the discrete events. FSTs can capture a general class of regular-rewriting attacks in which an attacker can nondeterministically rewrite sensing/actuation events according to a given regular relation. These include common insertion, deletion, event-wise replacement, and finite-memory replay attacks. We propose new theorems and algorithms with polynomial complexity to design resilient supervisors against these attacks. We also develop an open-source tool in Python based on the results and illustrate its applicability through a case study