摘要：A fuzzy clustering algorithm for intrusion detection based on heterogeneous attributes is proposed in this paper. Firstly, the algorithm modifies the comparability measurement for the categorical attributes according to the formula of Hemingway; then, for the shortages of fuzzy C-means clustering algorithm: initialize sensitively and easy to get into the local optimum, the presented new algorithm is optimized by GuoTao approach. We simulate our algorithm with the KDDCUP99 data set, and the results show that the convergence rate of the new algorithm is faster than the original fuzzy C-means clustering algorithm and the performance of our algorithm is more stable.
