Genetic algorithms can be used to obtain good linear congruential generators

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dc.contributor.author Hernández, Julio C.
dc.contributor.author Ribagorda, Arturo
dc.contributor.author Isasi Viñuela, Pedro
dc.contributor.author Sierra, José M.
dc.date.accessioned 2009-04-27T11:50:52Z
dc.date.available 2009-04-27T11:50:52Z
dc.date.issued 2001-07
dc.identifier.bibliographicCitation Cryptologia, 2001, vol. 25, n. 3, p. 213-229
dc.identifier.issn 1558-1586 (Online)
dc.identifier.uri http://hdl.handle.net/10016/4078
dc.description.abstract Linear Congruential Generators (LCGs) are one model of pseudorandom number generators used in a great number of applications. They strongly depend on, and are completely characterized by, some critical parameters. The selection of good parameters to define a LCG is a difficult task mainly done, nowadays, by consulting tabulated values [10] or by trial and error. In this work, the authors present a method based on genetic algorithms that can automatically solve the problem of finding good parameters for a LCG. They also show that the selection of an evaluation function for the generated solutions is critical to the problem and how a seemingly good function such as entropy could lead to poor results. Finally, other fitness functions are proposed and one of them is shown to produce very good results. Some other possibilities and variations that may produce fine linear congruential generators are also mentioned.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Taylor & Francis
dc.rights © Taylor & Francis
dc.subject.other Pseudorandom number generator
dc.subject.other Linear congruential generator
dc.subject.other Genetic algorithms
dc.subject.other Fitness function
dc.subject.other Security
dc.subject.other Entropy
dc.subject.other Period
dc.subject.other Randomness
dc.subject.other Randomness testing
dc.title Genetic algorithms can be used to obtain good linear congruential generators
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1080/0161-110191889897
dc.subject.eciencia Informática
dc.identifier.doi 10.1080/0161-110191889897
dc.rights.accessRights openAccess
dc.identifier.publicationfirstpage 213
dc.identifier.publicationissue 3
dc.identifier.publicationlastpage 229
dc.identifier.publicationtitle Cryptologia
dc.identifier.publicationvolume 25
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