Data-driven network intrusion detection using optimized machine learning algorithms
Network intrusion detection systems (NIDS) play a crucial role in maintaining cybersecurity by identifying malicious network activities. This study presents a comprehensive evaluation of machine learning approaches for network intrusion detection, comparing the performance of Decision Trees (DT), Ra...
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| Main Authors: | Dauda Adeite Adenusi, Oladosu Oyebisi Oladimeji, Theopilus Adekunle Oyekola, Korede Solomon Olagunju |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Franklin Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2773186325001276 |
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