Drift management in ML-based IoT device classification: A survey and evaluation

The fast-moving adaptation of the Internet of Things (IoT) and its devices has revolutionized the way we interact with the connecting things and perceive the world around us. Effective and efficient classification of these IoT devices is essential for network management, security, QoS and performanc...

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Bibliographic Details

Main Authors:	Waseem, Quadri, Wan Isni Sofiah, Wan Din, Azamuddin, Ab Rahman, Ali Khan, Arshad
Format:	Article
Language:	en en
Published:	Indonesian Society for Knowledge and Human Development 2024
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/40500/1/Drift%20Management%20in%20ML-Based%20IoT%20Device%20Classification.pdf http://umpir.ump.edu.my/id/eprint/40500/7/Drift%20Management%20in%20ML-Based%20IoT%20Device%20Classification%20A%20Survey%20and%20Evaluation.pdf http://umpir.ump.edu.my/id/eprint/40500/ https://doi.org/10.18517/ijaseit.15.3.13070
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