An Architecture for Network Intrusion Detection System Based on Dag Classification Using Hybrid Enesemble and Ensemble Method
Intrusion detection is an effective approach of dealing with problems in the area of network security. Rapid development in technology has raised the need for an effective intrusion detection system as the traditional intrusion detection method cannot compete against newly advanced intrusions. In this paper, the authors proposed a feature based intrusion data classification technique. The reduced feature improved the classification of intrusion data. The reduction process of feature attribute performs by DAG (Directed Acyclic Graph) function along with feature correlation factor. The proposed method work as feature reducers and classification technique, from the reduction of feature attribute also decrease the execution time of classification.