期刊
IEEE ACCESS
卷 7, 期 -, 页码 133190-133202出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2940729
关键词
Authentication; biometrics; data mining; gait recognition; identification; sensors; smartphone; smartwatch; ubiquitous computing
资金
- National Science Foundation [1116124]
Smartphones and smartwatches, which include powerful sensors, provide a readily available platform for implementing and deploying mobile motion-based behavioral biometrics. However, the few studies that utilize these commercial devices for motion-based biometrics are quite limited in terms of the sensors and physical activities that they evaluate. In many such studies, only the smartwatch accelerometer is utilized and only one physical activity, walking, is investigated. In this study we consider the accelerometer and gyroscope sensor on both the smartphone and smartwatch, and determine which combination of sensors performs best. Furthermore, eighteen diverse activities of daily living are evaluated for their biometric efficacy and, unlike most other studies, biometric identification is evaluated in addition to biometric authentication. The results presented in this article show that motion-based biometrics using smartphones and/or smartwatches yield good results, and that these results hold for the eighteen activities. This suggests that zero-effort continuous biometrics based on normal activities of daily living is feasible, and also demonstrates that certain easy-to-perform activities, such as clapping, may be a viable alternative (or supplement) to gait-based biometrics.
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