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dc.contributor.authorShahraki, Amin
dc.contributor.authorTaherkordi, Amir
dc.contributor.authorHaugen, Øystein
dc.date.accessioned2021-10-04T12:00:37Z
dc.date.available2021-10-04T12:00:37Z
dc.date.created2021-08-11T12:54:14Z
dc.date.issued2021
dc.identifier.citationComputer Networks. 2021, 194, Artikkel 108125.en_US
dc.identifier.issn1389-1286
dc.identifier.urihttps://hdl.handle.net/11250/2787479
dc.description.abstractInternet of Things (IoT) refers to a system of interconnected heterogeneous smart devices communicatingwithout human intervention. A significant portion of existing IoT networks is under the umbrella of ad-hoc andquasi ad-hoc networks. Ad-hoc based IoT networks suffer from the lack of resource-rich network infrastructuresthat are able to perform heavyweight network management tasks using, e.g. machine learning-based NetworkTraffic Monitoring and Analysis (NTMA) techniques. Designing light-weight NTMA techniques that do notneed to be (re-) trained has received much attention due to the time complexity of the training phase. In thisstudy, a novel pattern recognition method, called Trend-based Online Network Traffic Analysis (TONTA), isproposed for ad-hoc IoT networks to monitor network performance. The proposed method uses a statisticallight-weight Trend Change Detection (TCD) method in an online manner. TONTA discovers predominant trendsand recognizes abrupt or gradual time-series dataset changes to analyze the IoT network traffic. TONTA isthen compared with RuLSIF as an offline benchmark TCD technique. The results show that TONTA detectsapproximately 60% less false positive alarms than RuLSIF.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectInternet of Thingsen_US
dc.subjectIoTen_US
dc.subjectNTMAen_US
dc.subjectpattern recognitionen_US
dc.subjectnetwork traffic analysisen_US
dc.subjectnetwork monitoringen_US
dc.subjecttrend change detectionen_US
dc.titleTONTA: Trend-based Online Network Traffic Analysis in ad-hoc IoT networksen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2021 The Authors.en_US
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.source.pagenumber108125en_US
dc.source.volume194en_US
dc.source.journalComputer Networksen_US
dc.identifier.doi10.1016/j.comnet.2021.108125
dc.identifier.cristin1925308
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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