Towards probabilistic intrusion detection in supervisory control of discrete event systems

In control systems, sensor deception is a class of attacks where an attacker manipulates sensor readings to cause damage to the system. Our work investigates quantitative measurements to detect this class of attacks in the context of stochastic supervisory control. We introduce the notion of epsilon-safe systems, which is a first step to generalize qualitative intrusion detection conditions to quantitative intrusion detection conditions. We provide sufficient and necessary conditions to verify if a system is epsilon-safe. Moreover, we provide an algorithm that verifies these conditions, which implies that the problem is decidable. Copyright (C) 2020 The Authors.