Paper Title
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).