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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Comparison of Selection Methods and Crossover Operations using Steady State Genetic Based Intrusion Detection System

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Author Firas Alabsi, Reyadh Naoum
ISSN 2079-8407
On Pages 1053-1058
Volume No. 3
Issue No. 7
Issue Date July 01, 2012
Publishing Date July 01, 2012
Keywords Steady State Genetic Algorithm, Intrusion Detection System, Selection, Crossover


Abstract

Intrusion Detection Systems are systems built to detect the unwanted attacks. Genetic Algorithm is a method that mimics the process of natural evolution; it was used to support the Intrusion Detection Systems. Genetic Algorithm contains several elements such as population size, evaluation, encoding, crossover, mutation, replacement and stopping criterion. Elements specifications must be determined before using Genetic Algorithm. The performance of Genetic Algorithm depends mainly on these specifications. The aim of this paper is to compare different types of genetic operators and monitor their performance in Intrusion Detection System, to determine the Selection type and Crossover type to be worked together and perform better.  

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