Learning to Detect Anomalous Wireless Links in IoT Networks

dc.contributor.author	Cerar, Gregor
dc.contributor.author	Yetgin, Halil
dc.contributor.author	Bertalanic, Blaz
dc.contributor.author	Fortuna, Carolina
dc.date.accessioned	16/12/21 12:06
dc.date.available	16/12/21 12:06
dc.date.issued	2020
dc.identifier.issn	2169-3536
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10012
dc.identifier.uri	https://doi.org/10.1109/ACCESS.2020.3039333
dc.description.abstract	After decades of research, Internet of Things (IoT) is finally permeating real-life and helps improve the efficiency of infrastructures and processes as well as our health. As massive number of IoT devices are deployed, they naturally incurs great operati
dc.description.sponsorship	Slovenian Research AgencySlovenian Research Agency - Slovenia [P2-0016, J2-9232]
dc.language.iso	English
dc.publisher	Ieee-Inst Electrıcal Electronıcs Engıneers Inc
dc.rights	Green Submitted, gold
dc.source	Ieee Access
dc.title	Learning to Detect Anomalous Wireless Links in IoT Networks
dc.type	Article
dc.identifier.startpage	212130
dc.identifier.endpage	212155
dc.identifier.doi	10.1109/ACCESS.2020.3039333
dc.identifier.wos	WOS:000597200800001
dc.identifier.volume	8

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