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arXiv 1901.10312cs.CRcs.CVcs.CYcs.HC
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MultiLock: Mobile Active Authentication based on Multiple Biometric and Behavioral Patterns

Universidad Autonoma de Madrid(马德里自治大学)

Alejandro Acien, Aythami Morales, Ruben Vera-Rodriguez, Julian Fierrez

英文摘要:

In this paper we evaluate mobile active authentication based on an ensemble of biometrics and behavior-based profiling signals. We consider seven different data channels and their combination. Touch dynamics (touch gestures and keystroking), accelerometer, gyroscope, WiFi, GPS location and app usage are all collected during human-mobile interaction to authenticate the users. We evaluate two approaches: one-time authentication and active authentication. In one-time authentication, we employ the information of all channels available during one session. For active authentication we take advantage of mobile user behavior across multiple sessions by updating a confidence value of the authentication score. Our experiments are conducted on the semi-uncontrolled UMDAA-02 database. This database comprises smartphone sensor signals acquired during natural human-mobile interaction. Our results show that different traits can be complementary and multimodal systems clearly increase the performance with accuracies ranging from 82.2% to 97.1% depending on the authentication scenario.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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