دانلود مقاله ISI انگلیسی شماره 113104
ترجمه فارسی عنوان مقاله

ارزیابی عملکرد تأیید هویت تلفن های همراه با استفاده از تجزیه و تحلیل رفتار سنسور

عنوان انگلیسی
Performance evaluation of implicit smartphones authentication via sensor-behavior analysis
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
113104 2018 16 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Information Sciences, Volumes 430–431, March 2018, Pages 538-553

ترجمه کلمات کلیدی
امنیت تلفن هوشمند سنسورهای حرکتی احراز هویت بیومتریک، سنجش عملکرد،
کلمات کلیدی انگلیسی
Smartphone security; Motion sensors; Biometric authentication; Performance evaluation;
پیش نمایش مقاله
پیش نمایش مقاله  ارزیابی عملکرد تأیید هویت تلفن های همراه با استفاده از تجزیه و تحلیل رفتار سنسور

چکیده انگلیسی

The pervasiveness of mobile devices not only facilitates people’s daily life with a wide variety of services, but also brings users risks of private information leakage (e.g., photos, contact lists, bank accounts), which emphasizes the demand for reliable, feasible and user-friendly authentication mechanisms on mobile devices. In this paper, we develop an authentication mechanism using motion sensors (accelerometer and gyroscope) embedded in smartphones. Our proposed mechanism performs authentication continuously and implicitly by monitoring the user daily activities. We extract time-, frequency- and wavelet-domain features from motion-sensor data, and conduct empirical feature analysis to investigate the optimal combination of features, to acquire a fine-grained characterization of users’ movement patterns. To make a systematic performance evaluation, we have established a dataset containing 27,681 samples, including five kinds of actions and five different smartphone placements. In the evaluation procedure, four kinds of contexts are considered (nothing-aware context, action-aware context, placement-aware context and full-information-aware context), and ten one-class detectors are implemented. The best accuracy (represented as EER) for the four conditions achieves 28.22%, 2.21%, 5.50% and 3.28%, respectively, indicating our proposed approach is feasible and applicable in some real scenarios. Moreover, the performance analyses for sensor combinations and feature combinations are also conducted.