An empirical assessment of ML models for 5G network intrusion detection: a data leakage-free approach

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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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Bibliographic Details
Main Authors:	Bouke, Mohamed Aly, Abdullah, Azizol
Format:	Article
Language:	English
Published:	Elsevier 2024
Online Access:	http://psasir.upm.edu.my/id/eprint/113366/ http://psasir.upm.edu.my/id/eprint/113366/1/113366.pdf

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