Intrusion Detection Systems Using Decision Trees and Support Vector Machines

Security of computers and the networks that connect them is increasingly becoming of great significance. Intrusion detection is a mechanism of providing security to computer networks. Although there are some existing mechanisms for Intrusion detection, there is need to improve the performance. Data mining techniques are a new approach for Intrusion detection. In this paper we investigate and evaluate the decision tree data mining techniques as an intrusion detection mechanism and we compare it with Support Vector Machines (SVM). Intrusion detection with Decision trees and SVM were tested with benchmark 1998 DARPA Intrusion Detection data set. Our research shows that Decision trees gives better overall performance than the SVM.