System for attack recognition based on mining fuzzy association rules

In order to effectively reduces the false negative rate and false positive rate in attack recognition. This literature integrate fuzzy association rules to design and implement an abnormal network intrusion detection system. This system not only satisfies the requirements for attack recognition perfectly, but also recognizes the anomaly-based attacks and the misuse-based attacks simultaneously. Furthermore, it reduces the false negative rate.