Mathematical Model of Strong Physically Unclonable Functions Based on Hybrid Boolean Networks
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 $\mu_{inter}$ and reliability $\mu_{intra}$ obtained from experi...
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Zusammenfassung: | 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 $\mu_{inter}$ and reliability $\mu_{intra}$ 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. |
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DOI: | 10.48550/arxiv.2207.10816 |