A Fuzzy Clustering Approach for Intrusion Detection

Detection of intrusion attacks is an important issue in network security, now fuzzy set theory has been applied to many fields, therefore, research into fuzzy clustering method for knowledge is significant not only to theory, but also to application. the Fuzzy Possibility C-Means Algorithm for intrusion detection is adopted in this paper, the experiments with KDD Cup 1999 data demonstrate that our proposed method achieves 91.00% average detection rate, and the false positive rate ranges from 0.50% to 1.80%, the total performance evaluation is outperforms the RIPPER method.