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Empirical Study on Fusion Methods Using Ensemble of RBFNN for Network Intrusion Detection.

Authors :
Zhi-Qiang Liu
Xi-Zhao Wang
Hong Yan
Chan, Aki P.F.
Yeung, Daniel S.
Tsang, Eric C. C.
Ng, Wing W. Y.
Source :
Advances in Machine Learning & Cybernetics; 2006, p682-690, 9p
Publication Year :
2006

Abstract

The network security problem has become a critical issue and many approaches have been proposed to tackle the information security problems, especially the Denial of Service (DoS) attacks. Multiple Classifier System (MCS) is one of the approaches that have been adopted in the detection of DoS attacks recently. Fusion strategy is crucial and has great impact on the classification performance of an MCS. However the selection of the fusion strategy for an MCS in DoS problem varies widely. In this paper, we focus on the comparative study on adopting different fusion strategies for an MCS in DoS problem. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540335849
Database :
Supplemental Index
Journal :
Advances in Machine Learning & Cybernetics
Publication Type :
Book
Accession number :
32901492
Full Text :
https://doi.org/10.1007/11739685_71