Implementation of Support Vector Machines and Clustering of Intrusion Detection System for Computer Networks

Abstract

Considering that intrusion detection systems and anomaly clearly recognize malicious activity. Nowadays, data mining based intrusion detection systems, security and more rapidly detect attacks.Therefore,in this article we use a combination of k-means clustering algorithm and is used supervised support vector machine algorithm to find the best line separator. This is leading to the separation of normal and attack traffic.

Hybrid Intrusion Detection Model for Computer Networks

“…This trend will cause some repetitive and unnecessary features, which delay detection process, to be ignored. In this regard, adoption of an effective algorithm in feature selection is of great importance [2,3]. Several methods have been introduced in recent years to present an appropriate intrusion detection emphasizing feature selection.…”