Research of intrusion detection method based on rough set and adaptive boost

被引：0

作者：

Song Jian ^{[1
]}

Zou Muchun ^{[1
]}

Sun Wei ^{[1
]}

Zou Muchun ^{[1
]}

机构：

[1] Lanzhou Univ Technol, Sch Network, Lanzhou 730050, Peoples R China

来源：

ADVANCED COMPUTER TECHNOLOGY, NEW EDUCATION, PROCEEDINGS | 2007年

关键词：

intrusion detection; rough set; reduction; adaboost; classification;

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 intrusion detection method combining rough set with ADA-boost algorithm. In virtue of the ability rough set has to decease the amount of data and get rid of redundancy, the method can reduce the a-mount of ADAboost' training data used and improve running speed. Adaboost is a learning al-gorithm for constructing accurate classifiers. It can obtain a strong learning algorithm by combining a series of weak learning algorithms through some rules. The result of the experiment shows that this model has high detection rate.

引用

页码：142 / 145

页数：4

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