关键词: 入侵检测, 熵, 模糊聚类, 径向基函数神经网络

Abstract: In recent years，the neural network technology obtained the widespread application in the Intrusion，what most has represents is the BP neural network，but the local minimum nature of itself has limited the detection performance enhancement.The RBF network can solve the BP neural network existence question.But how to determine an appropriate RBF network hidden centers is also a difficult problem.In view of the above question，by combining Entropy-based Fuzzy Clustering（EFC） and neural network，this paper puts forward an improved RBF algorithm based on Entropy-based Fuzzy Clustering and applies this algorithm to intrusion detection.The experiment shows that algorithm can gains satisfying performances.

Key words: intrusion detection, entropy, fuzzy clustering, Radial Basis Function（RBF） neural network