An Anomaly Detection Method Based on Principal Component Analysis

Computer Engineering and Applications ›› 2006, Vol. 42 ›› Issue (21): 21-.

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An Anomaly Detection Method Based on Principal Component Analysis

武汉大学电子信息学院

Received:2006-02-08 Revised:1900-01-01 Online:2006-07-21 Published:2006-07-21

一种基于聚类和主成分分析的异常检测方法

汪阳,黄天戍,杜广宇

武汉大学电子信息学院

通讯作者: 汪阳 powerflow

Abstract

Abstract: An anomaly detection method based on principal component analysis is proposed. The method partitions the train data set into several sub-sets to get the distribution of the normal pattern in feature space. Then it extracts the feature contour of each sub-set. Finally it detects behavior records by the PCA matrix of each sub-set. The results of the experiment show that the anomaly detection method based on principal component analysis is effective.

Key words: Intrusion detection, Anomaly detection, Principal Component Analysis

摘要： 提出了一种基于主成分分析的异常检测方法，该方法利用聚类分析将训练数据划分为不同的子集，从而得到正常模式在特征空间中的分布，然后利用主成分分析来提取各行为子集的特征轮廓，最后利用各子集的PCA变换矩阵进行检测。实验结果证明了基于主成分分析的异常检测方法的有效性。

关键词: 入侵检测, 异常检测, 主成分分析

,,. An Anomaly Detection Method Based on Principal Component Analysis[J]. Computer Engineering and Applications, 2006, 42(21): 21-.

汪阳,黄天戍,杜广宇.

一种基于聚类和主成分分析的异常检测方法

[J]. 计算机工程与应用, 2006, 42(21): 21-.

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An Anomaly Detection Method Based on Principal Component Analysis

一种基于聚类和主成分分析的异常检测方法

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