Variationally universal hashing

Authors:
Ted Krovetz;Phillip Rogaway
Affiliations:
Department of Computer Science, California State University, Sacramento, CA;Department of Computer Science, University of California, Davis, CA and Department of Computer Science, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand
Venue:
Information Processing Letters
Year:
2006

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Abstract

The strongest well-known measure for the quality of a universal hash-function family H is its being ε-strongly universal, which measures, for randomly chosen h ∈ H, one's inability to guess h(m') even if h(m) is known for some m ≠ m' We give example applications in which this measure is too weak, and we introduce a stronger measure for the quality of a hash-function family, ε-variationally universal, which measures one's inability to distinguish h(m') from a random value even if h(m) is known for some m ≠ m'. We explain the utility of this notion and provide an approach for constructing efficiently compu table ε-VU hash-function families.