Study on Improved Fuzzy Clustering Algorithm in the Intrusion Detection

Article Abstract: Fuzzy C-means clustering algorithm is sensitive to its initialization of value,and its objective function is non-convex,easy to fall into local minimum points,while can＇t get the optimal solution.Combined with global fast-search capability of the particle swarm optimization algorithm,improved the objective function,and puts forward the improved fuzzy C-means clustering algorithm.Through theoretical analysis and experiments,show that the algorithm has better global optimal solution,overcomes the shortcomings of traditional fuzzy C-means clustering algorithm,can obtain satisfactory detection rate and false alarm rate in the intrusion detection.