Sensor-based Continuous Authentication of Smartphones' Users Using Behavioral Biometrics: A Contemporary Survey

Mobile devices and technologies have become increasingly popular, offering\ncomparable storage and computational capabilities to desktop computers allowing\nusers to store and interact with sensitive and private information. The\nsecurity and protection of such personal information are becoming more and more\nimportant since mobile devices are vulnerable to unauthorized access or theft.\nUser authentication is a task of paramount importance that grants access to\nlegitimate users at the point-of-entry and continuously through the usage\nsession. This task is made possible with today's smartphones' embedded sensors\nthat enable continuous and implicit user authentication by capturing behavioral\nbiometrics and traits. In this paper, we survey more than 140 recent behavioral\nbiometric-based approaches for continuous user authentication, including\nmotion-based methods (28 studies), gait-based methods (19 studies), keystroke\ndynamics-based methods (20 studies), touch gesture-based methods (29 studies),\nvoice-based methods (16 studies), and multimodal-based methods (34 studies).\nThe survey provides an overview of the current state-of-the-art approaches for\ncontinuous user authentication using behavioral biometrics captured by\nsmartphones' embedded sensors, including insights and open challenges for\nadoption, usability, and performance.\n