Fuzzy extractors (Dodis et al., Eurocrypt 2004) convert repeated noisy readings of a high-entropy secret into the same uniformly distributed key. A minimum condition for the security of the key is the hardness of guessing a value that is similar to the secret, because the fuzzy extractor converts such a guess to the key. We dene fuzzy min-entropy to quantify this property of a noisy source of secrets. Fuzzy minentropy measures the success of the adversary when provided with only the functionality of the fuzzy extractor, that is, the ideal security possible from a noisy distribution. High fuzzy min-entropy is necessary for the existence of a fuzzy extractor. We ask: is high fuzzy min-entropy a sucient condition for key extraction from noisy sources? If only computational security is required, recent progress on program obfuscation gives evidence that fuzzy min-entropy is indeed sucient. In contrast, information-theoretic fuzzy extractors are not known for many practically relevant sources of high fuzzy min-entropy. In this paper, we show that fuzzy min-entropy is also sucient for information-theoretically secure fuzzy extraction. For every source distribution W for which security is possible we give a secure fuzzy extractor. Our construction relies on the fuzzy extractor knowing the precise distribution of the source W . A more ambitious goal is to design a single extractor that works for all possible sources. We show that this more ambitious goal is impossible: we give a family of sources with high fuzzy min-entropy for which no single fuzzy extractor is secure. This result emphasizes the importance of accurate models of high entropy sources.
['Benjamin Fuller', 'Leonid Reyzin', 'Adam D. Smith']
When are Fuzzy Extractors Possible