Comparison of Selection Methods and Crossover Operations using Steady State Genetic Based Intrusion Detection System
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Full Text |
Pdf |
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Author |
Firas Alabsi, Reyadh Naoum
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ISSN |
2079-8407 |
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On Pages
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1053-1058
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Volume No. |
3
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Issue No. |
7
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Issue Date |
July 01, 2012 |
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Publishing Date |
July 01, 2012 |
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Keywords |
Steady State Genetic Algorithm, Intrusion Detection System, Selection, Crossover
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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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