In this paper, we investigate the feasibility of keystroke inference attacks on
handheld numeric touchpads by using smartwatch motion sensors as a side-channel.
The proposed attack approach employs supervised learning techniques to accurately
map the uniqueness in the captured wrist movements to each individual keystroke.
Experimental evaluation shows that keystroke inference using smartwatch motion
sensors is not only fairly accurate, but also better than similar attacks
previously demonstrated using smartphone motion sensors.