The Application of Multi-Class Support Vector Machines on Intrusion Detection System with the Feature Selection using Information Gain
Authors
Jihan Maharani, Zuherman Rustam
Corresponding Author
Jihan Maharani
Available Online August 2017.
- 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/).
Cite this article
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 -