Evolving hash functions by means of genetic programming

Proceedings of the 8th annual conference on Genetic and evolutionary computation. Seattle, Washington, USA, July 08-12, 2006The 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.This article has been financed by the Spanish founded research MCyT project OP:LINK, Ref:TIN2005-08818-C04-02.Publicad

Multicriteria evaluation of novel technologies for organic micropollutants removal in advanced water reclamation schemes for indirect potable reuse

Postprint (author's final draft

Finding state-of-the-art non-cryptographic hashes with genetic programming

Proceding of: 9th International Conference, Reykjavik, Iceland, September 9-13, 2006.The design of non-cryptographic hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this paper, we use the Genetic Programming paradigm to evolve collision free and fast hash functions. For achieving robustness against collision we use a fitness function based on a non-linearity concept, producing evolved hashes with a good degree of Avalanche Effect. The other main issue, 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.This article has been financed by the Spanish founded research MCyT project OP:LINK, Ref:TIN2005-08818-C04-02

Applications of an exact counting formula in the Bousso-Polchinski Landscape

The Bousso-Polchinski (BP) Landscape is a proposal for solving the Cosmological Constant Problem. The solution requires counting the states in a very thin shell in flux space. We find an exact formula for this counting problem which has two simple asymptotic regime one of them being the method of counting low $\Lambda$ states given originally by Bousso and Polchinski. We finally give some applications of the extended formula: a robust property of the Landscape which can be identified with an effective occupation number, an estimator for the minimum cosmological constant and a possible influence on the KKLT stabilization mechanism.Comment: 43 pages, 11 figures, 2 appendices. We have added a new section (3.4) on the influence of the fraction of non-vanishing fluxes in the KKLT mechanism. Other minor changes also mad