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2005
Springer

Anomaly Internet Network Traffic Detection by Kernel Principle Component Classifier

10 years 4 months ago
Anomaly Internet Network Traffic Detection by Kernel Principle Component Classifier
As a crucial issue in computer network security, anomaly detection is receiving more and more attention from both application and theoretical point of view. In this paper, a novel anomaly detection scheme is proposed. It can detect anomaly network traffic which has extreme large value on some original feature by the major component, or does not follow the correlation structure of normal traffic by the minor component. By introducing kernel trick, the nonlinearity of network traffic can be well addressed. To save the processing time, a simplified version is also proposed, where only major component is adopted. Experimental results validate the effectiveness of the proposed scheme.
Hanghang Tong, Chongrong Li, Jingrui He, Jiajian C
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ISNN
Authors Hanghang Tong, Chongrong Li, Jingrui He, Jiajian Chen, Quang-Anh Tran, Hai-Xin Duan, Xing Li
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