Type2Motion: Detecting Mobility Context from Smartphone Typing

Soumyajit Chatterjee, Bivas Mitra, Sandip Chakraborty

Abstract: Recent context detection techniques in smartphones leverage on the embedded motion sensors, which in turn increases the potential of side-channel attacks. We in this paper propose an alternative modality for obtaining mobility context using smartphone keyboard interaction patterns using a personalized framework. Experimental results show that the framework can predict the mobility context at an average F1 score (both micro and macro) greater than 0.6 across all subjects.