IACR News item: 18 April 2014
Ran Canetti, Benjamin Fuller, Omer Paneth, Leonid Reyzin
ePrint ReportWe construct the first fuzzy extractors that work for a large class of distributions that have negative minimum usable entropy. Their security is computational. They correct Hamming errors over a large alphabet. In order to avoid the worst-case loss, they necessarily restrict distributions for which they work.
Our first construction requires high individual entropy of a constant fraction of symbols, but permits symbols to be dependent. Our second construction requires a constant fraction of symbols to have a constant amount of entropy conditioned on prior symbols. The constructions can be implemented efficiently based on number-theoretic assumptions or assumptions on cryptographic hash functions.
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