Continuous-Source Fuzzy Extractors: Source uncertainty and insecurity

Fuller, Benjamin; Peng, Lowen

doi:10.1109/isit.2019.8849421

Cited by 7 publications

(1 citation statement)

References 37 publications

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“…Woodage et al [WCD + 17] subsequently improved the parameters. As a negative result, Fuller, Reyzin, and Smith [FRS16,FRS20] and Fuller and Peng [FP19] show families of distributions where no fuzzy extractor can simultaneously work for the whole family, despite the fact that a fuzzy extractor exists for each element of the family. Thus, two main open areas of research for informationtheoretic fuzzy extractors are providing polynomial-time constructions and providing constructions that simultaneously secure many distributions.…”

Section: Introductionmentioning

confidence: 99%

Computational fuzzy extractors

Fuller

Meng

Reyzin

2020

Information and Computation

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Fuzzy extractors derive strong keys from noisy sources. Their security is usually defined informationtheoretically, with gaps between known negative results, existential constructions, and polynomial-time constructions. We ask whether using computational security can close these gaps. We show the following: • Negative Result: Noise tolerance in fuzzy extractors is usually achieved using an information reconciliation component called a secure sketch. We show that secure sketches are subject to upper bounds from coding theory even when the information-theoretic security requirement is relaxed. Specifically, we define computational secure sketches using conditional HILL pseudoentropy (Håstad et al., SIAM J. Computing 1999). We show that a computational secure sketch implies an error-correcting code. Thus, HILL pseudoentropy is bounded by the size of the best error-correcting code. Similar bounds apply to information-theoretic secure sketches.

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Section: Introductionmentioning

confidence: 99%