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A Novel Intrusion Detection Model Based on Multi-layer Self-Organizing Maps and Principal Component Analysis.
- Source :
- Advances in Neural Networks - ISNN 2006 (9783540344827); 2006, p255-260, 6p
- Publication Year :
- 2006
-
Abstract
- In this paper, the Self Organizing Maps (SOM) learning and classification algorithms are firstly modified. Then via the introduction of match-degree, reduction-rate and quantification error of reducing sample, a novel approach to intrusion detection based on Multi-layered modified SOM neural network and Principal Component Analysis (PCA) is proposed. In this model, PCA is applied to feature selection, and Multi-layered SOM is designed to subdivide the imprecise clustering in single-layered SOM layer by layer. Experimental results demonstrate that this model can provide a precise and efficient way for implementing the classifier in intrusion detection. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783540344827
- Database :
- Supplemental Index
- Journal :
- Advances in Neural Networks - ISNN 2006 (9783540344827)
- Publication Type :
- Book
- Accession number :
- 32862408
- Full Text :
- https://doi.org/10.1007/11760191_37