Modeling intrusion detection system using hybrid intelligent systems

被引:210
|
作者
Peddabachigari, Sandhya
Abraham, Ajith [1 ]
Grosan, Crina
Thomas, Johnson
机构
[1] Chung Ang Univ, Sch Engn & Comp Sci, Seoul, South Korea
[2] Oklahoma State Univ, Dept Comp Sci, Stillwater, OK 74106 USA
[3] Univ Babes Bolyai, Dept Comp Sci, R-3400 Cluj Napoca, Romania
关键词
intrusion detection system; hybrid intelligent system; decision trees; support vector machines; ensemble approach;
D O I
10.1016/j.jnca.2005.06.003
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The process of monitoring the events occurring in a computer. system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). This paper presents two hybrid approaches for modeling IDS. Decision trees (DT) and support vector machines (SVM) are combined as a hierarchical hybrid intelligent system model (DT-SVM) and an ensemble approach combining the base classifiers. The hybrid intrusion detection model combines the individual base classifiers and other hybrid machine learning paradigms to maximize detection accuracy and minimize computational complexity. Empirical results illustrate that the proposed hybrid systems provide more accurate intrusion detection systems. (C) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:114 / 132
页数:19
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