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Título: | Privacy-Preserving Sensor-Based Continuous Authentication and User Profiling: A Review |
Autor: | Hernández-Álvarez, Luis CSIC ORCID; Fuentes, José María de; González-Manzano, Lorena; Hernández Encinas, Luis CSIC ORCID | Palabras clave: | Biometric databases Biometric features Continuous authentication Machine learning Privacy-preserving Sensor-based data User profiling |
Fecha de publicación: | 2020 | Editor: | Multidisciplinary Digital Publishing Institute | Citación: | Sensors 21(1): 92 (2021) | Resumen: | Ensuring the confidentiality of private data stored in our technological devices is a fundamental aspect for protecting our personal and professional information. Authentication procedures are among the main methods used to achieve this protection and, typically, are implemented only when accessing the device. Nevertheless, in many occasions it is necessary to carry out user authentication in a continuous manner to guarantee an allowed use of the device while protecting authentication data. In this work, we first review the state of the art of Continuous Authentication (CA), User Profiling (UP), and related biometric databases. Secondly, we summarize the privacy-preserving methods employed to protect the security of sensor-based data used to conduct user authentication, and some practical examples of their utilization. The analysis of the literature of these topics reveals the importance of sensor-based data to protect personal and professional information, as well as the need for exploring a combination of more biometric features with privacy-preserving approaches. | Descripción: | © 2020 by the authors. | Versión del editor: | https://doi.org/10.3390/s21010092 | URI: | http://hdl.handle.net/10261/225771 | DOI: | 10.3390/s21010092 | E-ISSN: | 1424-8220 |
Aparece en las colecciones: | (ITEFI) Artículos |
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Privacy_Preserving_Hernandez_Art2020.pdf | 328,12 kB | Adobe PDF | Visualizar/Abrir |
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