EyeTell: Video-Assisted Touchscreen Keystroke Inference from Eye Movements

Authors:
  • YCYimin Chen
    Yimin Chen
  • TLTao Li
    Tao Li
  • RZRui Zhang
    Rui Zhang
  • YZYanchao Zhang
    Yanchao Zhang
  • THTerri Hedgpeth
    Terri Hedgpeth
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Abstract
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.