EyeTell: Video-Assisted Touchscreen Keystroke Inference from Eye Movements
EyeTell: Video-Assisted Touchscreen Keystroke Inference from Eye Movements
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DOI：
10.1109/sp.2018.00010
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
Yimin Chen;Tao Li;Rui Zhang;Yanchao Zhang;Terri Hedgpeth
中科院分区：
文献类型：
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作者：
Yimin Chen;Tao Li;Rui Zhang;Yanchao Zhang;Terri Hedgpeth
击键推理攻击对无处不在的移动设备构成了越来越多的威胁。本文介绍了Eyetell，这是一种新颖的视频辅助攻击，可以通过视频捕捉他的眼睛动作来推断受害者在触摸屏设备上的击键。 Eyetell探讨了人眼自然关注并遵循其键入的键的观察，因此在软键盘上的打字顺序会导致独特的凝视痕迹连续的眼动。与先前的工作相反，Eyetell不要求攻击者在视觉上观察受害者的投入过程，也不需要将受害者装置放在静态持有人上。关于iOS和Android设备的综合实验证实了Eyetell在各种环境条件下推断引脚，锁定图案和英语单词的高效率。
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.