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In this paper, we consider the problem of synthesis of maximally permissivecovert damage-reachable attackers in the setup where the model of thesupervisor is unknown to the adversary but the adversary has recorded a(prefix-closed) finite set of observations of the runs of the closed-loopsystem. The synthesized attacker needs to ensure both the damage-reachabilityand the covertness against all the supervisors which are consistent with thegiven set of observations. There is a gap between the de facto maximalpermissiveness, assuming the model of the supervisor is known, and the maximalpermissiveness that can be attained with a limited knowledge of the model ofthe supervisor, from the adversary's point of view. We consider the setup wherethe attacker can exercise sensor replacement/deletion attacks and actuatorenablement/disablement attacks. The solution methodology proposed in this workis to reduce the synthesis of maximally permissive covert damage-reachableattackers, given the model of the plant and the finite set of observations, tothe synthesis of maximally permissive safe supervisors for certain transformedplant, which shows the decidability of the observation-assisted covert attackersynthesis problem. The effectiveness of our approach is illustrated on a watertank example adapted from the literature.

Synthesis of Maximally Permissive Covert Attackers Against Unknown Supervisors by Using Observations