An adaptive intrusion detection algorithm based on clustering and kernel-method

被引：0

作者：

Lee, Hansung ^{[1
]}

Chung, Yongwha ^{[1
]}

Park, Daihee ^{[1
]}

机构：

[1] Korea Univ, Dept Comp & Informat Sci, Seoul, South Korea

来源：

ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS | 2006年 / 3918卷

关键词：

intrusion detection; ART; mercer kernel; concept vector;

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：

An adaptive intrusion detection algorithm which combines the Adaptive Resonance Theory(ART) with the Concept Vector and the Mecer-Kernel is presented. Compared to the supervised- and the clustering-based Intrusion Detection Systems(IDSs), our algorithm can detect unknown types of intrusions in on-line by generating clusters incrementally.

引用

页码：603 / 610

页数：8

共 10 条

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