Multi-source Interactive Behavior Analysis for Continuous User Authentication on Smartphones

Xiaozi Liu, Chao Shen, Yufei Chen

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.