Touch gesture-based authentication on mobile devices: The effects of user posture, device size, configuration, and inter-session variability

Abstract Touch dynamics is a behavioral biometric that authenticates users by analyzing the characteristics of the touch gestures executed on mobile devices. Current research in this field has mostly focused on identifying the best algorithms and attributes to improve authentication performance. However, such systems must also be resilient against environmental variables. In this paper, we demonstrate that the user’s posture, device size and configuration have a significant impact on the performance of touch-based authentication systems. Our results indicate that authentication accuracy increases with the device size. Furthermore, we conclude that using a device’s 3-D orientation is necessary to attain better authentication performance. Our findings indicate that the features used in state-of-the-art touch-based authentication systems are insufficient to provide constant, reliable performance when any of the studied environmental variables change. With this paper, we release a new data set. Unlike the currently publicly available touch-based authentication datasets, our collection protocols control for all the studied variables. Our research study demonstrates threats to validity that noisy environmental conditions introduce to these currently available public datasets. This work is an extension of a previous publication. Presented user authentication approaches are unique and may have immediate benefits to the development of better touch-based authentication systems.