Research on Fuzzy Genetics-Based Rule Classifier in Intrusion Detection System

Intrusion detection technique has become the focus in the area of network security research. Various soft computing approaches have been applied to the intrusion detection field. The paper incorporate fuzzy logic and genetic algorithms into the classifying system based on fuzzy association rule to extract both accurate and interpretable fuzzy IF-THEN rules from network traffic data for classification, and utilize genetic algorithms to optimize the classifier. The experiments and evaluations of the proposed method were performed with the KDD Cup 99 intrusion detection dataset. Results indicate the high detection accuracy for intrusion attacks and low false alarm rate of the reliable system.