Incremental Hybrid Intrusion Detection Using Ensemble of Weak Classifiers

被引：0
|
作者：
Rasoulifard, Amin [1 ]
Bafghi, Abbas Ghaemi [1 ]
Kahani, Mohsen [1 ]
机构：
[1] Ferdowsi Univ Mashhad, Dept Comp Sci & Engn, Fac Engn, Mashhad, Iran
来源：
ADVANCES IN COMPUTER SCIENCE AND ENGINEERING | 2008年 / 6卷
关键词：
Hybrid intrusion detection system; Ensemble of Weak Classifiers; Incremental learning; KDD Cup 99 Dataset;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an incremental hybrid intrusion detection system is introduced. This system combines incremental misuse detection and incremental anomaly detection. It can learn new classes of intrusions that do not exist in the training dataset for incremental misuse detection. As the framework has low computational complexity, it is suitable for real-time or on-line learning. Also experimental evaluations on KDD Cup dataset are presented.
引用
收藏
页码：577 / 584
页数：8
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