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Optimizing Sensor Allocation Against Attackers With Uncertain Intentions: A Worst-Case Regret Minimization Approach | IEEE Journals & Magazine | IEEE Xplore

Optimizing Sensor Allocation Against Attackers With Uncertain Intentions: A Worst-Case Regret Minimization Approach


Abstract:

This letter focuses on the optimal allocation of multi-stage attacks with the uncertainty in attacker’s intention. We model the attack planning problem using a Markov dec...Show More

Abstract:

This letter focuses on the optimal allocation of multi-stage attacks with the uncertainty in attacker’s intention. We model the attack planning problem using a Markov decision process and characterize the uncertainty in the attacker’s intention using a finite set of reward functions—each reward represents a type of attacker. Based on this modeling, we employ the paradigm of the worst-case absolute regret minimization from robust game theory and develop mixed-integer linear program (MILP) formulations for solving the worst-case regret minimizing sensor allocation strategies for two classes of attack-defend interactions: one where the defender and attacker engage in a zero-sum game and another where they engage in a non-zero-sum game. We demonstrate the effectiveness of our algorithm using a stochastic gridworld example.
Published in: IEEE Control Systems Letters ( Volume: 7)
Page(s): 2863 - 2868
Date of Publication: 28 June 2023
Electronic ISSN: 2475-1456

Funding Agency:


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