Modeling Strong Physically Unclonable Functions with Metaheuristics
PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANION(2023)
摘要
Evolutionary algorithms have been successfully applied to attack Physically Unclonable Functions (PUFs). CMA-ES is recognized as the most powerful option for a type of attack called the reliability attack. In this paper, we take a step back and systematically evaluate several metaheuristics for the challenge-response pair-based attack on strong PUFs. Our results confirm that CMA-ES has the best performance, but we note several other algorithms with similar performance while having smaller computational costs.
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关键词
Metaheuristics,Physically Unclonable Functions,CMA-ES,CRP
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