A soft decision helper data algorithm for SRAM PUFs

In this paper we propose the idea of using soft decision information in helper data algorithms (HDA). We derive and verify a distribution for the responses of SRAM-based physically unclonable functions (PUFs) and show that soft decision information becomes available without loss in min-entropy of the fuzzy secret. This significantly improves the implementation overhead of using an SRAM PUF + HDA for cryptographic key generation compared to previous constructions.