Mathematical Model of Strong Physically Unclonable Functions Based on Hybrid Boolean Networks

TL;DR

This paper presents a mathematical model for Hybrid Boolean Network PUFs that accurately reproduces experimental statistics and demonstrates their potential as strong, secure PUFs with open-source simulation tools.

Contribution

It introduces a novel mathematical framework for simulating HBN-PUFs, validating it against experimental data, and analyzing their security properties.

Findings

Model reproduces experimental PUF statistics

HBN-PUFs are confirmed as strong PUFs with exponential security dependence

Open-source Python simulation tools are provided

Abstract

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.