A genetic SOM clustering algorithm for intrusion detection

Authors:
Zhenying Ma
Affiliations:
Department of Computer Science and Engineering, Chongqing University, Chongqing, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

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Abstract

By combining SOMs network and genetic algorithms, a genetic SOM (Self-Organizing Map) clustering algorithm for intrusion detection is proposed in this paper. In our algorithms, genetic algorithm is used to train the synaptic weights of SOMs. Computer experiments show that GSOMC produces good results on small data sets. Some discussions of the number of clusters K and future work is also given.