Abstract
Analyzing smartphone users’ behavioral characteristics for recognizing the identities has received growing interest from security and biometric researchers. Extant smartphone authentication methods usually provide one-time identity verification in some specific applications, but the authenticated user is still subject to masquerader attacks or session hijacking. This paper presents a novel smartphone authentication approach by analyzing multi-source user-machine usage behavior (i.e., power consumption, physical sensors, and touchscreen interactions), which can continuously verify the presence of a smartphone user. Extensive experiments are conducted to show that our authentication approach can be up to a relatively high accuracy with an equal-error rate of 5.5%. This approach can also be seamlessly integrated with existing authentication methods, which does not need additional hardware and is transparent to users.
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Acknowledgments
This research was supported in part by National Natural Science Foundation of China (U1736205, 61773310, 61403301), China Postdoctoral Science Foundation (2014M560783), Special Foundation of China Postdoctoral Science (2015T81032), Natural Science Foundation of Shaanxi Province (2015JQ6216), Application Foundation Research Program of SuZhou (SYG201444), Open Projects Program of National Laboratory of Pattern Recognition, and Fundamental Research Funds for the Central Universities (xjj2015115). Chao Shen is the corresponding author.
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Liu, X., Shen, C., Chen, Y. (2018). Multi-source Interactive Behavior Analysis for Continuous User Authentication on Smartphones. In: Zhou, J., et al. Biometric Recognition. CCBR 2018. Lecture Notes in Computer Science(), vol 10996. Springer, Cham. https://doi.org/10.1007/978-3-319-97909-0_71
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DOI: https://doi.org/10.1007/978-3-319-97909-0_71
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