A soft decision helper data algorithm for SRAM PUFs

Abstract
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.

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