Modeling Challenge Covariances and Design Dependency for Efficient Attacks on Strong PUFs

The physical unclonable function (PUF) is a widely used hardware security primitive. Many strong PUF designs have been proposed to resist non-invasive attacks leveraging acquired CRPs. In this work, we propose a general framework for efficient attacks on strong PUFs by investigating from two perspectives, namely, statistical covariances in the challenge space and the design dependency among PUF compositions. The framework consists of two novel attack methods against a wide range of PUF families, including XOR APUFs, interpose PUFs, and bistable ring (BR)-PUFs. We evaluate our proposed attacks through extensive experiments, running both software-based simulation and hardware implementations on FPGAs to compare with corresponding SOTA works. Much effort have been expended to maintain the same software/ hardware conditions for fair comparison. The results demonstrate that our framework significantly outperforms SOTA results. Moreover, we show that our framework can efficiently attack multiple PUF families built from entirely different types, while almost all existing works solely focused on attacking one or very limited number of PUF designs.