Exposure-Resilient Extractors

Authors:
Marius Zimand
Affiliations:
Towson University, USA
Venue:
CCC '06 Proceedings of the 21st Annual IEEE Conference on Computational Complexity
Year:
2006

Citing 0
Cited 2

Exposure-Resilient Extractors and the Derandomization of Probabilistic Sublinear Time

Computational Complexity
Pseudorandom Generators and Typically-Correct Derandomization

APPROX '09 / RANDOM '09 Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques

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Abstract

An exposure-resilient extractor is an efficient procedure that, from a random variable with imperfect min-entropy, produces randomness that passes all statistical tests including those that have bounded access to the random variable, with adaptive queries that can depend on the string beiing tested.