Multi-factor authentication for improved efficiency in ECG: Based login
| dc.contributor.author | Neves, P. | |
| dc.contributor.author | Nunes, L. | |
| dc.contributor.author | Lourenço, A. | |
| dc.contributor.editor | Fairclough, S., Holzinger, A., Otero, A., Pope, A., and Silva, H. P. da. | |
| dc.date.accessioned | 2021-10-14T13:36:38Z | |
| dc.date.available | 2021-10-14T13:36:38Z | |
| dc.date.issued | 2016-01-01 | |
| dc.date.updated | 2021-10-14T14:34:52Z | |
| dc.description.abstract | Electrocardiogram (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 identification | eng |
| dc.description.version | info:eu-repo/semantics/acceptedVersion | |
| dc.event.date | 2016 | |
| dc.event.location | Lisboa | eng |
| dc.event.title | 3rd International Conference on Physiological Computing Systems, PhyCS 2016 | |
| dc.event.type | Conferência | pt |
| dc.identifier.doi | 10.5220/0005936500670074 | |
| dc.identifier.isbn | 978-989-758-197-7 | |
| dc.identifier.issn | 2184-321X | |
| dc.identifier.uri | http://hdl.handle.net/10071/23333 | |
| dc.journal | PhyCS 2016 - Proceedings of the 3rd International Conference on Physiological Computing Systems | |
| dc.language.iso | eng | |
| dc.pagination | 67 - 74 | |
| dc.peerreviewed | yes | |
| dc.publisher | SciTePress | |
| dc.relation | info:eu-repo/grantAgreement/FCT/5876/147328/PT | |
| dc.rights | open access | |
| dc.subject | Biometrics | eng |
| dc.subject | Authentication | eng |
| dc.subject | Bluetooth | eng |
| dc.subject | Internet of things | eng |
| dc.title | Multi-factor authentication for improved efficiency in ECG: Based login | eng |
| dc.type | conferenceObject | |
| degois.publication.firstPage | 67 | |
| degois.publication.lastPage | 74 | |
| degois.publication.location | Lisboa | eng |
| degois.publication.title | Multi-factor authentication for improved efficiency in ECG: Based login | eng |
| dspace.entity.type | Publication | en |
| iscte.alternateIdentifiers.scopus | 2-s2.0-84991086149 | |
| iscte.alternateIdentifiers.wos | WOS:000387282000006 | |
| iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-76366 |
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