Multi-objective Particle Swarm Optimization in Intrusion Detection

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 32)

Abstract

In this paper, we proposed particle swarm optimization using multi-objective functions. Intrusion detection system has a significant role in research methodology. Intrusion detection system identifies the normal as well as abnormal behavior of a system. Swarm intelligence plays an essential role in intrusion detection. Random forest classifier is used for detecting attacks. Intrusion detection mechanism based on particle swarm optimization which has a strong global search capability is used for dimensionality optimization. Weighted aggregation method is employed as multi-objective functions. The proposed system has the high intrusion detection accuracy of 97.54 % with a detection time is 0.20 s.

Keywords

Particle swarm optimization Fitness function Multi-objective functions Swarm intelligence 

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSCMS School of Engineering and TechnologyErnakulamIndia

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