Modeling Strong Physically Unclonable Functions with Metaheuristics

Modeling Strong Physically Unclonable Functions with Metaheuristics

Coello, Carlos Coello
Krcek, M. (TU Delft Cyber Security)
Durasevic, Marko (University of Zagreb)
Mariot, L. (TU Delft Cyber Security; University of Twente)
Jakobovic, Domagoj (University of Zagreb)
Picek, S. (TU Delft Cyber Security; Radboud Universiteit Nijmegen)

2023

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.

CMA-ES
CRP
Metaheuristics
Physically Unclonable Functions

http://resolver.tudelft.nl/uuid:677406cc-6eb9-48ce-ab84-c3a1e89795e2

https://doi.org/10.1145/3583133.3590699

Association for Computing Machinery (ACM)

2024-02-05

9798400701207

GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

2023 Genetic and Evolutionary Computation Conference Companion, GECCO 2023 Companion, 2023-07-15 → 2023-07-19, Lisbon, Portugal

GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2023 Carlos Coello Coello, M. Krcek, Marko Durasevic, L. Mariot, Domagoj Jakobovic, S. Picek