论文标题
基于混合布尔网络的强大物理函数的数学模型
Mathematical Model of Strong Physically Unclonable Functions Based on Hybrid Boolean Networks
论文作者
论文摘要
我们介绍了一个数学框架，用于模拟混合布尔网络（HBN）物理上无可吻合的功能（PUF，HBN-PUFS）。我们验证该模型能够重现实验观察到的PUF统计数据的唯一性$μ__{inter} $和可靠性$μ__{intra} $，从旋风v fpgas上的HBN-PUFS实验中获得。我们的结果表明，HBN-PUF是一个真正的“强” PUF，因为其安全性属性在制造业变化和挑战 - 响应空间上都取决于其安全性。我们的Python仿真方法是开源的，可在https://github.com/noeloikeau/networkm上找到。
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 $μ_{inter}$ and reliability $μ_{intra}$ 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.
