Privacy-Preserving Sensor-Based Continuous Authentication and User Profiling: A Review

被引:27
作者
Hernandez-alvarez, Luis [1 ]
Maria de Fuentes, Jose [2 ]
Gonzalez-Manzano, Lorena [2 ]
Hernandez Encinas, Luis [1 ]
机构
[1] CSIC, Inst Phys & Informat Technol ITEFI, C Serrano 144, Madrid 28006, Spain
[2] Univ Carlos III Madrid, Comp Secur Lab COSEC, Madrid 28911, Spain
关键词
biometric databases; biometric features; continuous authentication; machine learning; privacy-preserving; sensor-based data; user profiling; BIOMETRIC TEMPLATE PROTECTION; ACTIVE AUTHENTICATION; SECURE; FACE; COMPUTATION; FRAMEWORK; KEYS;
D O I
10.3390/s21010092
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
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页码:1 / 23
页数:23
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