文章基本信息

标题：Improve Intrusion Detection Using Decision Tree with Sampling
本地全文：下载
作者：Devendra kailashiya ; Dr. R.C. Jain
期刊名称：International Journal of Computer Technology and Applications
电子版ISSN：2229-6093
出版年度：2012
卷号：3
期号：3
页码：1209-1216
出版社：Technopark Publications
摘要：Intrusion detection system used to discover illegitimate and unnecessary behavior at accessing or manipulating computer systems. The present paper aims to improve accuracy Rate of intrusion detection using decision tree algorithm. Intrusion detection systems aim to identify attacks with a high detection rate and a low Error rate. In this paper we have supervised learning with preprocessing step for intrusion detection. I using the stratified Weighted sampling techniques to generate the samples from original dataset. These sampled applied on the proposed algorithm. The accuracy of proposed model is compared with existing results in order to verify the validity and accuracy of the proposed model. The results showed that the proposed approach gives better and robust representation of data. The experiments and evaluations of the proposed intrusion detection system are performed with the KDD Cup 99 dataset. The experimental results clearly show that the proposed system achieved higher Accuracy and Low Error in identifying whether the records are normal or attack one.
关键词：Intrusion Detection; Decision Tree; KDD Cup 99 dataset; Stratified Weighted Sampling; Data preprocessing and ID3.