Universiti Teknologi Malaysia Institutional Repository

Anomaly network intrusion detection method in network security based on principle component analysis

Chimphlee, Witcha and Md Sap, Mohd Noor and Abdullah, Abdul Hanan and Chimphlee, Siriporn (2006) Anomaly network intrusion detection method in network security based on principle component analysis. Jurnal Teknologi Maklumat, 18 (2). pp. 114-124. ISSN 0128-3790

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Abstract

Most current intrusion detection methods cannot process large amounts of audit data for real-time operation. In this paper, anomaly network intrusion detection method based on Principle Component Analysis (PCA) for data reduction and classifier in presented. Each network connection is transformed into an input data vector. Moreover, PCA is applied to reduce the high dimensional data vectors and distance between a vector, and its projection onto the subspace. Based on the preliminary analysis using a set of benchmark data from KDD (Knowledge Discovery and Data Mining) Competition designed by DARPA, PCA demonstrates the ability to reduce huge dimensional data into a lower dimensional subspace without losing important information. This finding can be used to further enhance the detection accuracy in detecting new types of intrusion by taking PCA as the preprocessing requirement in reducing high dimensional data.

Item Type:Article
Uncontrolled Keywords:Anomaly detection, principal component analysis, high dimensional data, vector, covariance matrix
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:3288
Deposited By: Mrs Rozilawati Dollah @ Md Zain
Deposited On:22 May 2007 04:49
Last Modified:01 Jun 2010 03:08

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