Using SVM and Clustering Algorithmsin IDS Systems.

Intrusion Detection System (IDS) is a system, that monitors network traffic and tries to detect suspicious activity. In this paper we discuss the possibilities of application of clustering algorithms and Support Vector Machines (SVM) for use in the IDS. There we used K-means, FarthestFirst and COBWEB algorithms as clustering algorithms and SVM as classification SVM of type 1, known too as C-SVM. By appropriate choosing of kernel and SVM parameters we achieved improvements in detection of intrusion to system. Finally, we experimentally verified the efficiency of applied algorithms in IDS.