An Intelligent Intrusion Detection System Using Outlier Detection and Multiclass SVM

Intrusion Detection Systems have been used along with various techniques to detect intrusions in networks, distributed databases and web databases. However, all these systems are able to detect the intruders with high false alarm rate. In this paper, we propose a new intrusion detection model using the combination of outlier detection method and multiclass SVM classification. For this purpose, we propose a new outlier detection algorithm called Weighted Distance Based Outlier Detection algorithm (WDBOD) and an Enhanced Multiclass Support Vector Machine algorithm for detecting the intruders. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high detection rate when tested with KDD Cup 99 data set.