Towards a scalable intrusion detection system based on parallel PSO clustering using mapreduce

Authors:
Ibrahim Aljarah;Simone A. Ludwig
Affiliations:
North Dakota State University, Fargo, ND, USA;North Dakota State University, Fargo, ND, USA
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

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Abstract

The growing data traffic in large networks faces new challenges requiring efficient intrusion detection systems. The analysis of this high volume of data traffic to discover attacks has to be done very quickly. However, in order to be able to process large data, new distributed and parallel methods need to be developed. Several approaches are proposed to build intrusion systems using clustering approaches. In this paper, we introduce an intrusion detection system based on a parallel particle swarm optimization clustering algorithm using the MapReduce framework. The proposed system is scalable in processing large data on commodity hardware.