计算机工程与应用2012，Vol.48Issue(30)：117-121,5.DOI:10.3778/j.issn.1002-8331.2012.30.025
非负矩阵分解降维的入侵检测方法
Intrusion detection classification method based on non-negative matrix factorization
摘要
Abstract
The curse of dimensionality would arise when high dimensional network connection records are directly processed. So it is usually required to reduce dimensionality of the records. Non-negative matrix factorization not only can reduce dimensionality, but also makes all elements in the factor matrices non-negative, which corresponds to the semantic feature of the network connection records. After high dimensional network connection records are projected into low dimensional visual space by non-negative matrix factorization, network connection records are represented as scatter dots in low dimensional space. The class to which the record belongs is determined by observing the location of the scatter dot, and intrusion detection is visualized. Experiments demonstrate the effectiveness of this intrusion detection method.关键词
入侵检测/非负矩阵分解/可视化Key words
intrusion detection/ non-negative matrix factorization/ visualization分类
信息技术与安全科学引用本文复制引用
刘积芬..非负矩阵分解降维的入侵检测方法[J].计算机工程与应用,2012,48(30):117-121,5.基金项目
上海海事大学科研项目(No.201100051). （No.201100051）
