Intrusion detection system based on multi-class SVM

被引：0

作者：

Lee, H ^{[1
]}

Song, J ^{[1
]}

Park, D ^{[1
]}

机构：

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

来源：

ROUGH SETS, FUZZY SETS, DATA MINING, AND GRANULAR COMPUTING, PT 2, PROCEEDINGS | 2005年 / 3642卷

关键词：

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, we propose a new intrusion detection system: MMIDS (Multi-step Multi-class Intrusion Detection System), which alleviates some drawbacks associated with misuse detection and anomaly detection. The MMIDS consists of a hierarchical structure of one-class SVM, novel multi-class SVM, and incremental clustering algorithm: Fuzzy-ART. It is able to detect novel attacks, to give detail informations of attack types, to provide economic system maintenance, and to provide incremental update and extension with a system.

引用

页码：511 / 519

页数：9

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