Classification of Network Movements with KNN in Network Attack Prevention Systems
The Intrusion Detection Systems important part of computer and network security. There are many intrusion
detection systems classified network activities as normal or abnormal by using intelligent techniques. In this study, normal
and abnormal (R2L, U2R, DOS) network traffic movements are classified by using artificial neural networks and KNN
classification methods. In our experimental tests, we used KDDCup99 network traffic data which is frequently used in the
literature. High accuracy classification results obtained in our study are shown
Keywords- KDD 99, Intrusion Detection System (IDS), K-Nearest Neighbor (KNN).