(Smart)watch your taps Article Swipe

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Smartwatch Keystroke logging Computer science Inference Motion (physics) Mobile device Artificial intelligence Keystroke dynamics Human–computer interaction Computer vision Wearable computer Machine learning Computer security Embedded system Operating system S/KEY Password

Anindya Maiti , Murtuza Jadliwala , Jwu‐Sheng Hu , Igor Bilogrevic ·

YOU? · · 2015 · Open Access · · DOI: https://doi.org/10.1145/2802083.2808397 · OA: W2081706043

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.