Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/23333
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Campo DCValorIdioma
dc.contributor.authorNeves, P.-
dc.contributor.authorNunes, L.-
dc.contributor.authorLourenço, A.-
dc.contributor.editorFairclough, S., Holzinger, A., Otero, A., Pope, A., and Silva, H. P. da.-
dc.date.accessioned2021-10-14T13:36:38Z-
dc.date.available2021-10-14T13:36:38Z-
dc.date.issued2016-01-01-
dc.identifier.isbn978-989-758-197-7-
dc.identifier.issn2184-321X-
dc.identifier.urihttp://hdl.handle.net/10071/23333-
dc.description.abstractElectrocardiogram (ECG) based biometrics have proven to be a reliable source of identification. ECG can now be measured off-the-person, requiring nothing more than dry electrodes or conductive fabrics to acquire a usable ECG signal. However, identification still has a relatively poor performance when using large user databases. In this paper we suggest using ECG authentication associated with a smartphone security token in order to improve performance and decrease the time required for the recognition. This paper reposts the implementation of this technique in a user authentication scenario for a Windows login using normal Bluetooth (BT) and Bluetooth Low Energy (BLE). This paper also uses Intel Edison’s mobility features to create a more versatile environment. Results proved our solution to be feasible and present improvements in authentication times when compared to a simple ECG identificationeng
dc.language.isoeng-
dc.publisherSciTePress-
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147328/PT-
dc.rightsopenAccess-
dc.subjectBiometricseng
dc.subjectAuthenticationeng
dc.subjectBluetootheng
dc.subjectInternet of thingseng
dc.titleMulti-factor authentication for improved efficiency in ECG: Based logineng
dc.typeconferenceObject-
dc.event.title3rd International Conference on Physiological Computing Systems, PhyCS 2016-
dc.event.typeConferênciapt
dc.event.locationLisboaeng
dc.event.date2016-
dc.pagination67 - 74-
dc.peerreviewedyes-
dc.journalPhyCS 2016 - Proceedings of the 3rd International Conference on Physiological Computing Systems-
degois.publication.firstPage67-
degois.publication.lastPage74-
degois.publication.locationLisboaeng
degois.publication.titleMulti-factor authentication for improved efficiency in ECG: Based logineng
dc.date.updated2021-10-14T14:34:52Z-
dc.description.versioninfo:eu-repo/semantics/acceptedVersion-
dc.identifier.doi10.5220/0005936500670074-
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-76366-
iscte.alternateIdentifiers.wosWOS:000387282000006-
iscte.alternateIdentifiers.scopus2-s2.0-84991086149-
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