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

被引：0

作者：

Charlot, Noeloikeau ^{[1
]}

Gauthier, Daniel J. ^{[1
]}

Canaday, Daniel ^{[2
]}

Pomerance, Andrew ^{[2
]}

机构：

[1] Ohio State Univ, Dept Phys, 174 W 18th Ave, Columbus, OH 43210 USA

[2] Potomac Res LLC, Alexandria, VA USA

来源：

2022 IEEE INTERNATIONAL SYMPOSIUM ON HARDWARE ORIENTED SECURITY AND TRUST (HOST) | 2022年

关键词：

Hybrid Boolean Network (HBN); Physically Unclonable Function (PUF); Field Programmable Gate Array (FPGA);

D O I：

10.1109/HOST54066.2022.9840173

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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 littps://github.com/Noelloikeau/networkm.

引用

页码：129 / 132

页数：4

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