An Improved Ant-IS Algorithm for Intrusion Detection

Amal Miloud-Aouidate and Ahmed Riadh Baba-Ali
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Amal Miloud-Aouidate: University of Science and Technology Houari Boumediene, Algiers, Algeria
Ahmed Riadh Baba-Ali: University of Science and Technology Houari Boumediene, Algiers, Algeria

International Journal of Applied Metaheuristic Computing (IJAMC), 2014, vol. 5, issue 1, 65-78

Abstract: During recent years, the number of attacks on networks has dramatically increased. Consequently the interest in network intrusion detection has increased among the researchers. This paper proposes a clustering Ant-IS and an active Ant colony optimization algorithms for intrusion detection in computer networks. The goal of these algorithms is to extract a set of learning instances from the initial training dataset. The proposed algorithms are an improvement of the previously presented Ant-IS algorithm, used is pattern recognition. Results of experimental tests show that the proposed algorithms are capable of producing a reliable intrusion detection system.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jamc00:v:5:y:2014:i:1:p:65-78

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