The Application of Multi-Class Support Vector Machines on Intrusion Detection System with the Feature Selection using Information Gain

DOI

10.2991/icomse-17.2018.1How to use a DOI?

Keywords

Information gain, Intrusion detection system, Support vector machine

Abstract

Nowadays, the intrusions often occur in a network system. One of ways that Intrusions can be prevented or detected is by using Intrusion Detection System. Therefore, IDS (Intrusion Detection System) is indispensable to detect intrusions in a network. In this paper, we will discuss the classification of IDS’s data using Multi-class SVM with Information Gain Feature Selection and for the data used KDD Cup Dataset. As a result, we will discuss the accuracy of SVM combined with information gain feature selection.

Copyright

© 2018, 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  - Jihan Maharani
AU  - Zuherman Rustam
PY  - 2017/08
DA  - 2017/08
TI  - The Application of Multi-Class Support Vector Machines on Intrusion Detection System with the Feature Selection using Information Gain
BT  - Proceedings of the 1st Annual International Conference on Mathematics, Science, and Education (ICoMSE 2017)
PB  - Atlantis Press
SP  - 1
EP  - 3
SN  - 2352-5398
UR  - https://doi.org/10.2991/icomse-17.2018.1
DO  - 10.2991/icomse-17.2018.1
ID  - Maharani2017/08
ER  -