Nurudeen M. IbrahimMoussa Mahamat Boukar2025-01-212023-02-02Udoh, Godwil E. et.al. (2023). Network Intrusion Detection using a Hybridized Harmony Search and Random Forest. The 2nd International Conference on Multidisciplinary Engineering and Applied Sciences (ICMEAS-2023)979-8-3503-5883-4DOI: 10.1109/ICMEAS58693.2023.10429865https://repository.nileuniversity.edu.ng/handle/123456789/157Intrusion Detection Systems are used to find security holes in a system. However, a number of factors, including irrelevant information, contribute to intrusion detection system's low detection accuracy. This work presents a hybrid intrusion detection system (IDS) that combines the Random Forest algorithm and Harmony Search to address this issue and increase IDS detection accuracy. The proposed method was analyzed using NSL-KDD, and the experiment results show that the model functions effectively.enIntrusion DetectionMachine LearningFeature SelectionHarmony Search Algorithm.Article