Earticle

Physical unclonable functions (PUFs) have outstanding unique and non-reproducible properties owing to inter-chip variations. However, the amount of randomness in a PUF output could be a significant limitation. In this study, by passing the PUF response to a shift register, the randomness of the PUF output can be greatly increased while maintaining reliability. We discuss the performance of an arbiter-type PUF and a ring-oscillator-type PUF with a simple shift register from the viewpoint of biometrics. Moreover, PUFs, particularly linear delay-based PUFs, are not designed for machine learning or linear programming, which makes innovation difficult. We further focus on an efficient PUF evaluation method by using linear programming and logistic regression in the case of the challenge response pairs (CRPs) with low entropy.