Intrusion Detection Based on Support Vector Machine Divided Up by Clusters

被引：0

作者：

Li, Yong ^{[1
]}

Qian, Yuwen ^{[2
]}

机构：

[1] Anyang Normal Univ, Coll Educ Informat Technol, Anyang, Henan, Peoples R China

[2] Nanjing Univ Sci & Technol, Sch Automat, Nanjing, Zhejiang, Peoples R China

来源：

2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL VII | 2010年

关键词：

Intrusion Detection Support; Vector Machine; Clustering;

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 order to reduce SVM's (Support Vector Machine) high complexity of time, we propose a new method based on SVM divided up by clusters in this paper. The training set are divided into many subsets by clustering algorithm, and the new date will be classified by the decision function of the cluster to which it belongs. The experiment results for the intrusion detection data classification show that our method can detect intrusion action quickly and accurately.

引用

页码：284 / 286

页数：3

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