Authentication on the Go: Assessing the Effect of Movement on Mobile Device Keystroke Dynamics

Transparent authentication based on behavioral biometrics has the potential to improve the usability of mobile authentication due to the lack of a possibly intrusive user interface. Keystroke dynamics, or typing behavior, is a potentially rich source of biometric information for those that type frequently, and thus has been studied widely as an authenticator on touch-based mobile devices. However, the typing-while-moving scenario that characterizes mobile device use may change keystroke-based patterns sufficiently that typing biometrics-based authentication may not be viable. This paper presents a user study on the effects of user movement while typing on the effectiveness of keystroke dynamics as an authenticator. Using the dynamic text-based keystroke timings of 36 study participants, we first show that naïvely measuring patterns without considering position (e.g., sitting, standing or walking while typing) results in generic patterns that are little better than chance. We show that first determining the user's position before classifying their typing behavior, our two-phased approach, inferred the user's position with an AUC of above 90%, and the user's typing pattern was classified with an AUC of over 93%. Our results show that user typing patterns are a viable secondary or continuous post-PIN authentication method, even when movement changes a user's typing pattern.