EyeTell: Video-Assisted Touchscreen Keystroke Inference from Eye Movements
Yimin Chen, Tao Li, Rui Zhang, Yanchao Zhang, Terri Hedgpeth
摘要
Keystroke inference attacks pose an increasing threat to ubiquitous mobile devices. This paper presents EyeTell, a novel video-assisted attack that can infer a victim's keystrokes on his touchscreen device from a video capturing his eye movements. EyeTell explores the observation that human eyes naturally focus on and follow the keys they type, so a typing sequence on a soft keyboard results in a unique gaze trace of continuous eye movements. In contrast to prior work, EyeTell requires neither the attacker to visually observe the victim's inputting process nor the victim device to be placed on a static holder. Comprehensive experiments on iOS and Android devices confirm the high efficacy of EyeTell for inferring PINs, lock patterns, and English words under various environmental conditions. II. RELATED WORK In this section, we discuss the prior work most related to EyeTell in two research directions: keystroke inference attacks and eye-tracking-related security implications.
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