Volume 11, Number 3

Multi-Layer Classifier for Minimizing False Intrusion


Shaker El-Sappagh, Ahmed saad Mohammed and Tarek Ahmed AlSheshtawy, Benha University, Egypt


Intrusion detection is one of the standard stages to protect computers in network security framework from several attacks. False alarms problem is critical in intrusion detection, which motivates many researchers to discover methods to minify false alarms. This paper proposes a procedure for classifying the type of intrusion according to multi-operations and multi-layer classifier for handling false alarms in intrusion detection. The proposed system is tested using on KDDcup99 benchmark. The performance showed that results obtained from three consequent classifiers are better than a single classifier. The accuracy reached 98% based on 25 features instead of using all features of KDDCup99 dataset


Intrusion detection, multi-layer classifier, KDD CUP 99, False Alarms