Design of an Intrusion Detection Model for IoT-Enabled Smart Home

Machine learning (ML) provides effective solutions to develop efficient intrusion detection system (IDS) for various environments. In the present paper, a diversified study of various ensemble machine learning (ML) algorithms has been carried out to propose design of an effective and time-efficient...

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Veröffentlicht in:	IEEE access Jg. 11; S. 1
Hauptverfasser:	Rani, Deepti, Gill, Nasib Singh, Gulia, Preeti, Arena, Fabio, Pau, Giovanni
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms and intrusion detection systems (IDS) Boosting Classification algorithms Classifiers Communications traffic Cybersecurity Efficiency ensemble classifiers False alarms gradient boosting algorithms Internet of Things Intrusion detection Intrusion detection systems intrusion detection systems (IDS) light gradient boosting machines (LGBM) Machine learning Machine learning algorithms Machine learning classification algorithms Model accuracy Performance measurement Smart buildings Telecommunication traffic Traffic models
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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