Synthesis of Maximally Permissive Covert Attackers Against Unknown Supervisors by Using Observations
Ruochen Tai, Liyong Lin, Yuting Zhu, Rong Su

TL;DR
This paper develops a method to synthesize maximally permissive covert attackers against unknown supervisors using recorded observations, ensuring damage reachability and covertness despite limited model knowledge.
Contribution
It introduces a novel approach to synthesize covert attackers with maximal permissiveness using finite observations, bridging the gap from known to unknown supervisor models.
Findings
Decidability of the observation-assisted covert attacker synthesis problem.
Reduction of attacker synthesis to safe supervisor synthesis for transformed plant.
Effective application demonstrated on a water tank example.
Abstract
In this paper, we consider the problem of synthesis of maximally permissive covert damage-reachable attackers in the setup where the model of the supervisor is unknown to the adversary but the adversary has recorded a (prefix-closed) finite set of observations of the runs of the closed-loop system. The synthesized attacker needs to ensure both the damage-reachability and the covertness against all the supervisors which are consistent with the given set of observations. There is a gap between the de facto maximal permissiveness, assuming the model of the supervisor is known, and the maximal permissiveness that can be attained with a limited knowledge of the model of the supervisor, from the adversary's point of view. We consider the setup where the attacker can exercise sensor replacement/deletion attacks and actuator enablement/disablement attacks. The solution methodology proposed in…
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Taxonomy
TopicsSecurity and Verification in Computing · Smart Grid Security and Resilience · Cryptography and Data Security
