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Peixin Qu
Henan Institute of Science and Technology

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Network Intrusion Detection Based on PSO-SVM Changsheng Xiang; Yong Xiao; Peixin Qu; Xilong Qu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In order to improve network intrusion detection precision, this paper proposed a network intrusion detection model based on simultaneous selecting features and parameters of support vector machine (SVM) by particle swarm optimization (PSO) algorithm. Firstly, the features and parameters of SVM are coded to particle, and then the PSO is used to find the  optimal features and SVM parameters by collaboration among particles, lastly, the performance of the model was tested by KDD Cup 99 data. Compared with other network models, the proposed model has reduced input features for SVM and has significantly improved the detection precision of network intrusion. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3826
Co-Authors Changsheng Xiang Xilong Qu Yong Xiao