Detecting targeted interference in NB-IoT

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dc.contributor.authorMorillo, Gabrielaen
dc.contributor.authorRoedig, Utzen
dc.contributor.authorPesch, Dirken
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2023-06-20T15:18:52Z
dc.date.available2023-06-20T15:18:52Z
dc.date.issued2023-06en
dc.description.abstractMany Internet of Things (IoT) applications are considered critical systems, and it is important to guarantee that such deployments are resilient to attacks. An attacker may use radio interference selectively to disrupt communication while minimising the risk of their detection. It is essential to identify such attacks in order to remove the threat. In this work, we propose a novel method of detecting targeted interference in a Narrowband Internet of Things (NB-IoT) network at the User Equipment (UE). NB-IoT is a recent Low Power Wide Area Network (LPWAN) radio technology used to deploy IoT infrastructures at scale. Network performance data collected at the UE is used to reason about the current interference situation. Subframe loss rates within the downlink channel are monitored and used as input for a statistical anomaly detector. Our evaluation shows that the detector is able to distinguish targeted interference attacks from the impact of naturally occurring interference in cellular networks. This is important as naturally occurring interference requires a different response than targeted interference attacks.en
dc.description.sponsorshipScience Foundation Ireland (13/RC/2077 P2)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMorillo, G., Roedig, U. and Pesch, D. (2023) 'Detecting targeted interference in NB-IoT', 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Coral Bay, Pafos, Cyprus, June 19-21, pp. 475-482. https://doi.org/10.1109/DCOSS-IoT58021.2023.00080en
dc.identifier.doi10.1109/DCOSS-IoT58021.2023.00080
dc.identifier.eissn2325-2944
dc.identifier.endpage482
dc.identifier.isbn979-8-3503-4649-7
dc.identifier.isbn979-8-3503-4650-3
dc.identifier.issn2325-2936
dc.identifier.startpage475
dc.identifier.urihttps://hdl.handle.net/10468/14681
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Centres for Research Training Programme::Data and ICT Skills for the Future/18/CRT/6222/IE/SFI Centre for Research Training in Advanced Networks for Sustainable Societies/en
dc.rights© 2023, the Authors. For the purpose of Open Access, the authors have applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Version of Record: © 2023, IEEE.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectInternet of Thingsen
dc.subjectNarrowband Internet of Thingsen
dc.subjectJammingen
dc.subjectAnomaly Detectionen
dc.titleDetecting targeted interference in NB-IoTen
dc.typeConference itemen
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