Efficient Testing of Physically Unclonable Functions for Uniqueness

Abstract

Physically unclonable functions (PUFs) have emerged as lightweight hardware security primitives for implementing secure authentication. Strong PUFs rely on random manufacturing process variation to create unique Boolean mappings from input (challenge) to output (output). For secure authentication, challenge to response mappings are required to be unique for each device. However, uniqueness is not guaranteed by design or manufacturing. Testing for uniqueness and weeding out non-unique parts are the only way to ensure uniqueness of devices. Uniqueness testing can be expensive in time as the challenge-responses of the N th device under-test, must be proven to be different from previously tested N - 1 devices, or the device must be discarded. To reduce the time complexity of uniqueness testing, Multi-Index hashing (MIH) was proposed for online testing in high volume manufacturing. Database search using MIH was shown to be fast, but it suffers from high memory cost. In this paper, we address the memory problem of MIH based uniqueness testing by proposing alternative MIH strategies. Our results indicate that the proposed search strategies can significantly reduce the memory cost without sacrificing performance, requiring ≈ 3.35× less memory with just a 17% performance overhead when testing the uniqueness of 1 million PUFs.