Phases vs. Levels using Decision Trees for Intrusion Detection Systems

Security of computers and the networks that connect them is increasingly becoming of great significance. Intrusion detection system is one of the security defense tools for computer networks. This paper compares two different model Approaches for representing intrusion detection system by using decision tree techniques. These approaches are Phase-model approach and Level-model approach. Each model is implemented by using two techniques, New Attacks and Data partitioning techniques. The experimental results showed that Phase approach has higher classification rate in both New Attacks and Data Partitioning techniques than Level approach. Keywords-component; network intrusion detection; Decision Tree; NSL-KDD dataset; network security