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dc.contributor.authorGurulian, Iakovosen_NZ
dc.contributor.authorShepherd, Carltonen_NZ
dc.contributor.authorFrank, Eibeen_NZ
dc.contributor.authorMarkantonakis, Konstantinosen_NZ
dc.contributor.authorAkram, Raja Naeemen_NZ
dc.contributor.authorMayes, Keithen_NZ
dc.coverage.spatialSydney, Australiaen_NZ
dc.date.accessioned2018-08-21T22:13:27Z
dc.date.available2017-01-01en_NZ
dc.date.available2018-08-21T22:13:27Z
dc.date.issued2017en_NZ
dc.identifier.citationGurulian, I., Shepherd, C., Frank, E., Markantonakis, K., Akram, R. N., & Mayes, K. (2017). On the effectiveness of ambient sensing for detecting NFC Relay Attacks. In Proceedings of 2017 IEEE Trustcom/BigDataSE/ICESS (pp. 41–49). Washington, DC, USA: IEEE. https://doi.org/10.1109/Trustcom/BigDataSE/ICESS.2017.218en
dc.identifier.issn2324-9013en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/12030
dc.description.abstractSmartphones with Near-Field Communication (NFC) may emulate contactless smart cards, which has resulted in the deployment of various access control, transportation and payment services, such as Google Pay and Apple Pay. Like contactless cards, however, NFC-based smartphone transactions are susceptible to relay attacks, and ambient sensing has been suggested as a potential countermeasure. In this study, we empirically evaluate the suitability of ambient sensors as a proximity detection mechanism for smartphone-based transactions under EMV constraints. We underpin our study using sensing data collected from 17 sensors from an emulated relay attack test-bed to assess whether they can thwart such attacks effectively. Each sensor, where feasible, was used to record 350-400 legitimate and relay (illegitimate) contactless transactions at two different physical locations. Our analysis provides an empirical foundation upon which to determine the efficacy of ambient sensing for providing a strong anti-relay mechanism in security-sensitive applications. We demonstrate that no single, evaluated mobile ambient sensor is suitable for such critical applications under realistic deployment constraints.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherIEEEen_NZ
dc.rightsThis is an author’s accepted version of an article published in the Proceedings of 2017 IEEE Trustcom/BigDataSE/ICESS. © 2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
dc.source16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications / The 11th IEEE International Conference on Big Data Science and Engineering / The 14th IEEE International Conference on Embedded Software and Systemsen_NZ
dc.subjectScience & Technologyen_NZ
dc.subjectTechnologyen_NZ
dc.subjectComputer Science, Information Systemsen_NZ
dc.subjectComputer Science, Theory & Methodsen_NZ
dc.subjectComputer Scienceen_NZ
dc.subjectrelay attacksen_NZ
dc.subjectambient sensingen_NZ
dc.subjectmobile securityen_NZ
dc.subjectcontactless transactionsen_NZ
dc.subjectnear-field communication (NFC)en_NZ
dc.subjectAUTHENTICATIONen_NZ
dc.subjectMachine learning
dc.titleOn the effectiveness of ambient sensing for detecting NFC Relay Attacksen_NZ
dc.typeConference Contribution
dc.identifier.doi10.1109/Trustcom/BigDataSE/ICESS.2017.218en_NZ
dc.relation.isPartOfProceedings of 2017 IEEE Trustcom/BigDataSE/ICESSen_NZ
pubs.begin-page41
pubs.declined2017-06-19T12:35:37.862+1200
pubs.elements-id194833
pubs.end-page49
pubs.finish-date2017-08-04en_NZ
pubs.place-of-publicationWashington, DC, USA
pubs.publication-statusPublisheden_NZ
pubs.start-date2017-08-01en_NZ


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