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Proceedings Paper

Optimizing radial basis function networks to recognize network attacks for intrusion detection
Author(s): Wei Pan; Weihua Li; Haobin Shi; Jianfeng Yan
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Paper Abstract

A methodology for optimizing radial basis function (RBF) networks is proposed, which consists of the RBF network and the self-organizing map (SOM), aiming at improving the performance of the recognition and classification of novel attacks for intrusion detection. The optimal network architecture of the RBF network is determined automatically by the improved SOM algorithm, in which the centers and the number of hidden neurons are self-adjustable. The intrusion feature vectors are extracted from a benchmark dataset (the KDD-99) designed by DARPA. The experimental results demonstrate that the proposed approach to recognize network attacks performance especially in terms of both efficient and accuracy.

Paper Details

Date Published: 4 January 2006
PDF: 5 pages
Proc. SPIE 5985, International Conference on Space Information Technology, 59851V (4 January 2006); doi: 10.1117/12.657359
Show Author Affiliations
Wei Pan, Northwestern Polytechnical Univ. (China)
Weihua Li, Northwestern Polytechnical Univ. (China)
Haobin Shi, Northwestern Polytechnical Univ. (China)
Jianfeng Yan, Northwestern Polytechnical Univ. (China)

Published in SPIE Proceedings Vol. 5985:
International Conference on Space Information Technology
Cheng Wang; Shan Zhong; Xiulin Hu, Editor(s)

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