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GECCO
2006
Springer

Evolving hash functions by means of genetic programming

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Evolving hash functions by means of genetic programming
The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fast hash functions. We use a fitness function based on a non-linearity measure, producing evolved hashes with a good degree of Avalanche Effect. Efficiency is assured by using only very fast operators (both in hardware and software) and by limiting the number of nodes. Using this approach, we have created a new hash function, which we call gp-hash, that is able to outperform a set of five human-generated, widely-used hash functions. Categories and Subject Descriptors H.4 [Information Systems Applications]: Miscellaneous General Terms Algorithms Keywords Hash functions, genetic programming, avalanche effect
César Estébanez, Julio César
Added 23 Aug 2010
Updated 23 Aug 2010
Type Conference
Year 2006
Where GECCO
Authors César Estébanez, Julio César Hernández Castro, Arturo Ribagorda, Pedro Isasi
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