Eliminating leakage in reverse fuzzy extractors

In recent years Physically Unclonable Functions (PUFs) have been proposed as a promising building block for security related scenarios like key storage and authentication. PUFs are physical systems and as such their responses are inherently noisy, precluding a straightforward derivation of cryptographic key material from raw PUF measurements. To overcome this drawback, Fuzzy Extractors are used to eliminate the noise and guarantee robust outputs. A special type are Reverse Fuzzy Extractors, shifting the computational load of error correction towards a computationally powerful verifier. However, the Reverse Fuzzy Extractor reveals error patterns to any eavesdropper, which may cause privacy issues (if the PUF key is drifting, the error pattern is linkable to the identity) and even security problems (if the noise is data-dependent and multiple protocol transcripts can be linked to the same user). In this work we investigate this leakage and propose a modified protocol that eliminates the problem. Keywords: Physically Unclonable Functions, Fuzzy Extractors, Authentication, Privacy, Security