Network Intrusion Detection using a Hybridized Harmony Search and Random Forest

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dc.contributor.authorNurudeen M. Ibrahim
dc.contributor.authorMoussa Mahamat Boukar
dc.date.accessioned2025-01-21T11:29:53Z
dc.date.issued2023-02-02
dc.description.abstractIntrusion 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.
dc.identifier.citationUdoh, 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)
dc.identifier.other979-8-3503-5883-4
dc.identifier.uriDOI: 10.1109/ICMEAS58693.2023.10429865
dc.identifier.urihttps://repository.nileuniversity.edu.ng/handle/123456789/157
dc.language.isoen
dc.publisherInternational Conference on Multidisciplinary Engineering and Applied Science
dc.subjectIntrusion Detection
dc.subjectMachine Learning
dc.subjectFeature Selection
dc.subjectHarmony Search Algorithm.
dc.titleNetwork Intrusion Detection using a Hybridized Harmony Search and Random Forest
dc.typeArticle

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