An efficient fuzzy extractor for limited noise
A fuzzy extractor is a security primitive that allows 
for reproducible extraction of an almost uniform key from a 
non-uniform noisy source. We analyze a fuzzy extractor scheme that 
uses universal hash functions for both information reconciliation and 
privacy amplification. This is a useful scheme when the number of 
error patterns likely to occur is limited, regardless of the error 
probabilities. We derive a sharp bound on the uniformity of the 
extracted key, making use of the concatenation property of universal 
hash functions and a recent tight formulation of the leftover hash 
lemma.