Using incremental learning method for adaptive network intrusion detection

被引：0
|
作者：
Yang, W [1 ]
Yun, XC [1 ]
Zhang, LJ [1 ]
机构：
[1] Harbin Engn Univ, Informat Secur Res Ctr, Harbin 150001, Peoples R China
来源：
Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年
关键词：
network security; intrusion detection; incremental rule learning; adaptivity;
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：
This paper proposes an adaptive on-line intrusion detection model based on incremental rule learning. This model can make self-learning over the ever-emerged new network behavior examples and dynamically modify behavior profile of the model, which overcomes the disadvantage that the traditional static detecting model must relearn over all the old and new examples, even can't relearn because of limited memory size. The experiment results validate the feasibility and effectivity of the presented adaptive intrusion detection model.
引用
收藏
页码：3932 / 3936
页数：5
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