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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Espín López, Juan Manuel | - |
dc.contributor.author | Huertas Celdrán, Alberto | - |
dc.contributor.author | Marín-Blázquez, Javier G. | - |
dc.contributor.author | Esquembre, Francisco | - |
dc.contributor.author | Martínez Pérez, Gregorio | - |
dc.contributor.other | Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Matemáticas | es |
dc.contributor.other | Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Ingeniería de la Información y las Comunicaciones | - |
dc.date.accessioned | 2024-01-23T11:47:26Z | - |
dc.date.available | 2024-01-23T11:47:26Z | - |
dc.date.issued | 2021-05-28 | - |
dc.identifier.citation | Sensors 2021, 21, 3765 | es |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | http://hdl.handle.net/10201/137590 | - |
dc.description | © 2021. The authors. This document is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by /4.0/ This document is the Accepted version of a Published Work that appeared in final form in Sensors. | es |
dc.description.abstract | Continuous authentication systems have been proposed as a promising solution to au- thenticate users in smartphones in a non-intrusive way. However, current systems have important weaknesses related to the amount of data or time needed to build precise user profiles, together with high rates of false alerts. Voice is a powerful dimension for identifying subjects but its suitability and importance have not been deeply analyzed regarding its inclusion in continuous authentication systems. This work presents the S3 platform, an artificial intelligence-enabled continuous authen- tication system that combines data from sensors, applications statistics and voice to authenticate users in smartphones. Experiments have tested the relevance of each kind of data, explored different strategies to combine them, and determined how many days of training are needed to obtain good enough profiles. Results showed that voice is much more relevant than sensors and applications statistics when building a precise authenticating system, and the combination of individual models was the best strategy. Finally, the S3 platform reached a good performance with only five days of use available for training the users’ profiles. As an additional contribution, a dataset with 21 volun- teers interacting freely with their smartphones for more than sixty days has been created and made available to the community. | es |
dc.format | application/pdf | es |
dc.format.extent | 33 | es |
dc.language | eng | es |
dc.publisher | MDPI | es |
dc.relation | This research was partially funded by the European Commission through 5GZORRO project (Grant No. 871533) part of the 5G PPP in Horizon 2020, by the Spanish Ministry of Science and Innovation through projects MTM2017-84079-P and PID2019-108377RB-C32, by the Swiss Federal Office for Defense Procurement (armasuisse) with the CyberSpec (CYD-C-2020003) project, and by the University of Zürich UZH. | es |
dc.rights | info:eu-repo/semantics/openAccess | es |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Continuous authentication | es |
dc.subject | Smartphone | es |
dc.subject | Sensors | es |
dc.subject | Applications usage | es |
dc.subject | Speaker recognition | es |
dc.subject | Artificial intelligence | es |
dc.subject.other | CDU::6 - Ciencias aplicadas | es |
dc.title | S3: An AI-Enabled User Continuous Authentication for Smartphones Based on Sensors, Statistics and Speaker Information | es |
dc.type | info:eu-repo/semantics/article | es |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/21/11/3765 | es |
dc.identifier.doi | https://doi.org/10.3390/s21113765 | - |
Aparece en las colecciones: | Artículos: Matemáticas |
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