Network Intrusion Detection Model Based on Combination Algorithm Selecting Features

doi:10.3969/j.issn.1006-2475.2014.08.017

Abstract

Abstract:

In order to improve the detection accuracy of network intrusion, this paper proposed a network intrusion

detection model based on combination algorithm selecting features. Firstly, the mathematical model of network

intrusion detection features selecting problem is established, and then genetic algorithm is used to find the

feasible sub-features, and the optimal sub-features is obtained by particle swarm optimization algorithm, finally,

the network intrusion detection model is established by relevance vector machine, and the performance is test by

simulation experiments. The test results show that the proposed model can not only improved the detection speed,

but also can improve the network intrusion detection accuracy.

Key words: , feature selection； intrusion detection； genetic algorithm； particle swarm optimization algorithm

CLC Number:

TP393.08

LIU Chun. Network Intrusion Detection Model Based on Combination Algorithm Selecting Features[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.08.017.

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