NIDS using Random Forest and Random Tree - Mohanapriya, K; Devi, M. Savitha (International Journal of Computer Sciences and Engineering, 2025)
Network Intrusion Detection Systems (NIDS) is the most important system in cyber security and it informs network administrators about policy violations. Identifying the network security violations and tells about where administrators to be improved. In Existing NIDS is designed to detect known network attacks. In this paper it is proposed to develop systematic methods for classifying intrusion detection. The key ideas are to use data mining techniques to discover network behaviour, anomalies and known Intrusions. Decision trees have been effectively used in NIDS but suffer from over sampling and the tree splitting being greedy locally. To overcome this some of the ensemble techniques like Random Forest, Random Trees and Ensemble Weak Learner Tree (EWL TREE) are used. Proposed technique reduces the number of trees required and also improves the precision and recall.