  Evolutionary algorithms have been successfully applied to attacking
Physically Unclonable Functions (PUFs). CMA-ES is recognized as the most
powerful option for a type of attack called the reliability attack. While there
is no reason to doubt the performance of CMA-ES, the lack of comparison with
different metaheuristics and results for the challenge-response pair-based
attack leaves open questions if there are better-suited metaheuristics for the
problem.
  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 also note several
other algorithms with similar performance while having smaller computational
costs. More precisely, if we provide a sufficient number of challenge-response
pairs to train the algorithm, various configurations show good results.
Consequently, we conclude that EAs represent a strong option for
challenge-response pair-based attacks on PUFs.
