Insertion attack identification in discrete event systems using petri nets with an observer.

Abstract

This study addresses the problem of attack identification in discrete event systems modeled with Petri nets, focusing specifically on sensor attacks that mislead observers to making incorrect decisions. Insertion attacks are one of the sensor attacks that are considered in this work. First, we formulate a novel observation structure to systematically model insertion attacks within the Petri net framework. Second, by generating an extended reachability graph that incorporates the observation structure, we can find a special class of markings whose components can have negative markings. Third, an observation place is computed by formulating an integer linear programming problem, enabling precise detection of attack occurrences. The occurrence of an attack can be identified by the number of tokens in the designed observation place. Finally, examples are provided to verify the proposed approach. Comparative analysis with existing techniques demonstrates that the reported approach offers enhanced detection accuracy and robustness, making it a significant advancement in the field of secure discrete event systems.