We introduce a mathematical framework for simulating Hybrid Boolean Network (HBN) Physically Unclonable Functions (PUFs, HBN-PUFs). We verify that the model is able to reproduce the experimentally observed PUF statistics for uniqueness μinter and reliability μintra obtained from experiments of HBN-PUFs on Cyclone V FPGAs. Our results suggest that the HBN-PUF is a true `strong' PUF in the sense that its security properties depend exponentially on both the manufacturing variation and the challenge-response space. Our Python simulation methods are open-source and available at https://github.com/Noeloikeau/networkm.
@article{arxiv.2207.10816,
title = {Mathematical Model of Strong Physically Unclonable Functions Based on Hybrid Boolean Networks},
author = {Noeloikeau Charlot and Daniel J. Gauthier and Daniel Canaday and Andrew Pomerance},
journal= {arXiv preprint arXiv:2207.10816},
year = {2024}
}
Comments
Presented at HOST 2022 conference. This work has been submitted to the IEEE for possible publication