This paper investigates the problem of synthesizing network attacks against fault diagnosis in the context of discrete event systems (DESs). It is assumed that the sensor observations sent to the operator that monitors a system are tampered with by an active attacker. We first formulate the process of online fault diagnosis under attack. Then, from the attack viewpoint, we define a sensor network attacker as successful if it can degrade the fault diagnosis in the case of maintaining itself as undiscovered by the operator. To verify such an attacker, an information structure called a joint diagnoser (JD) is proposed, which describes all possible attacks in a given attack scenario. Based on the refined JD, i.e., stealthy joint diagnoser (SJD), we present an algorithmic procedure for synthesizing a successful attacker if it exists.

This paper addresses the verification of fault predictability under attack in discrete event systems modeled with finite state automata. A sensor attacker can launch attacks on the observations sent from sensors to an operator that monitors a system. A novel notion of robust predictability against attacks is provided, which captures the features that the occurrence of any fault can be predicted prior to its occurrence despite the case of sensor attacks. We propose a test automaton that describes all possible attacks in a given attack scenario. Based on it, a necessary and sufficient condition for robust predictability verification is presented. Then, from the attacker's viewpoint, we provide the notion of a successful attacker that can destroy fault predictability and keep stealthy from the system operator. It is shown that a stealthy test automaton, can be used for verifying the existence of successful attackers.