Increasing the detection rate of intrusions to the networks by using the decision trees

Security is one of the most important issues in modern computer systems. Among the major challenges in these systems is identifying normal and abnormal behaviors. But the boundary between these two is not well defined and it is a very complicated task to accomplish. Intrusion detection systems are one of the techniques that are used to maintain security in computer networks. Incorrect report of the intrusion alarm system is one of the major problems of security systems. Intrusion is defined as a set of activities and the purpose of these activities is jeopardizing the integrity, reliability and unauthorized system access to a particular resource.This paper proposes a mechanism based on the decision tree technique to detect intrusions in the network. Simulation results show that by the proposed method not only the duration of the training phase was reduced but also the detection rate and false alarm rate were improved.