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.