A RO-Integrated-LFSR-Based Nonlinear Strong PUF with Intrinsic Modeling Attacks Resilience

Physical Unclonable Functions (PUF) are important hardware security primitives used for generating keys and identity authentication, with wide applications in the Internet of Things security. However, the security of strong PUF faces serious threats from modeling attacks, especially in the case of Arbiter PUF and their variants that involve additive linear integration of entropy sources. This paper proposes a Ring-Oscillator-Integrated-Linear-Feedback-Shift-Register-based PUF (ROinLFSR PUF) that achieves immunity to modeling attacks by highly nonlinearly integrating independent responses from weak RO PUFs using a configurable LFSR. To increase the efficiency of entropy extraction in hardware resources, dual entropy sources extraction is performed on the period and duty cycle of RO. Python simulation and FPGA experimental results demonstrate that the proposed PUF has intrinsic resilience against modeling attacks. And the proposed PUF achieves good results in reliability, uniqueness, uniformity, and randomness.