Intrusion detection based on data mining

被引：0

作者：

Yin, Jian ^{[1
]}

Mei, Fang ^{[1
]}

Zhang, Gang ^{[1
]}

机构：

[1] Sun Yat Sen Univ, Dept Comp Sci, Guangzhou 510275, Peoples R China

来源：

COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS | 2006年 / 4114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：

Many traditional algorithms use single metric generated by multi-events to detect intrusion by comparison with a certain threshold. In this paper we present a metric vector-based algorithm to detect intrusion while introducing the sample distance for both discrete and continuous data in order to improve the algorithm on heterogeneous dataset. Experiments on MIT lab Data show that the proposed algorithm is effective and efficient.

引用

页码：724 / 729

页数：6

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