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Mansour Sheikhan and Maryam Sharifi Rad Using particle swarm optimization in fuzzy association rules-based feature selection and fuzzy ARTMAP-based attack recognition Security and Communication Networks 6

Version of Record online: 13 AUG 2012 | DOI: 10.1002/sec.609

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In this study, a fuzzy association rules mining-based feature selection method is proposed for use in the attack recognizers of computer networks. To improve the performance, particle swarm optimization algorithm is employed to determine optimum parameter values of rule-mining and feature-mining modules; in addition to training parameters of fuzzy ARTMAP neural classifier. When compared with some other machine learning methods, the proposed system indicates better performance in terms of detection rate, false alarm rate, and cost per example.

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