A Detection Method of Network Intrusion Based on SVM and Ant Colony Algorithm

DOI

10.2991/citcs.2012.237How to use a DOI?

Keywords

Network Defense; Intrusion Detection; Support Vector Machine (SVM); Ant Colony Algorithm

Abstract

This paper researches the intrusion detection problem of the network defense, pointing at the problem of low fitting defects in the traditional detection algorithm of high precision and low forecasting accuracy under the situation of small sample training, and puts forward the algorithm of Support Vector Machine. Aimed at the important influence of SVM kernel function on classification performance, this paper adopts the improved Ant Colony Algorithm as the method of selection SVM characteristics parameters. Experiments show this algorithm is significantly higher than the other algorithm in training and the detection speed, and have a high enhance of the detection rates of attacking sample.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jianfeng Pu
AU  - Lizhi Xiao
AU  - Yanzhi Li
AU  - Xingwen Dong
PY  - 2012/11
DA  - 2012/11
TI  - A Detection Method of Network Intrusion Based on SVM and Ant Colony Algorithm
BT  - Proceedings of the 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 932
EP  - 935
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.237
DO  - 10.2991/citcs.2012.237
ID  - Pu2012/11
ER  -