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Proceedings Paper

Research of the network intrusion detection method based on support vector machine
Author(s): Ying Tang; Lixin Xu
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Paper Abstract

For the growing web intrusion issues, we propose a new method for intrusion detection. In this paper, statistical learning theory (SLT) is introduced to intrusion detection and a method based on support vector machine (SVM) is presented. Theory of SVM is introduced first, and then in data pretreatment, we propose a method of reducing the dimension of primal data sets and a method of transforming eigenvalue from characters to numbers. In virtue of the network data sets which appear variable, small and with high dimension, we introduce the Sequential Minimal Optimization (SMO) algorithm which is especially for large scale problems. The testing result based on the DARPA data show that the method is effective and efficient.

Paper Details

Date Published: 5 March 2008
PDF: 11 pages
Proc. SPIE 6623, International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing, 662318 (5 March 2008); doi: 10.1117/12.791498
Show Author Affiliations
Ying Tang, Beijing Institute of Technology (China)
Lixin Xu, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 6623:
International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing

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