A VC Dimension-Oriented Improvement Method of PUFs for the Anti-Modeling-Attack Capability
Yongliang Chen, Xiaole Cui, Sunrui Zhang, Xiaoxin Cui · ACM Transactions on Embedded Computing Systems · 2025
The physical unclonable function (PUF) serves as a security primitive of circuits, which is applicable to the embedded systems with lightweight authentication function. However, the modeling attack, which estimates the unknown CRPs by establishing the mathematical model of PUF, is a real threat to the PUF based crypto-systems. Subsequently, the anti-modeling-attack PUF becomes a research hotspot. The systematic design method of secure PUF is still an open issue, although some secure PUF schemes have been proposed based on the repeated trials. This work proposes a security improvement method of PUFs to enhance the anti-modeling-attack capability. The growth function and the Vapnik-Chervonenkis (VC) dimension of PUF are defined as the indicators of PUF security. The proposed method regards the improvement of PUF as an optimization problem, which aims to obtain a PUF scheme with the better security indicators. Guided by the indicators, the proposed method is able to specify the improvement sites of PUF and the techniques to be applied. In addition, three approaches are proposed to inspire the new security improvement techniques. An improved arbiter PUF and an improved array-based PUF are designed as the instances of the results from the proposed method. Both of the improved PUF schemes have the stronger security than the original schemes.