An empirical assessment of ML models for 5G network intrusion detection: a data leakage-free approach
This paper thoroughly compares thirteen unique Machine Learning (ML) models utilized for Intrusion detection systems (IDS) in a meticulously controlled environment. Unlike previous studies, we introduce a novel approach that meticulously avoids data leakage, enhancing the reliability of our findings...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/113366/1/113366.pdf http://psasir.upm.edu.my/id/eprint/113366/ https://linkinghub.elsevier.com/retrieve/pii/S2772671124001700 |
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