(Smart)watch your taps: side-channel keystroke inference attacks using smartwatches
(Smart)watch your taps: side-channel keystroke inference attacks using smartwatches
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DOI：
10.1145/2802083.2808397
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发表时间：
2015-09
期刊：
影响因子：
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通讯作者：
Anindya Maiti;Murtuza Jadliwala;Jibo He;Igor Bilogrevic
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文献类型：
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作者：
Anindya Maiti;Murtuza Jadliwala;Jibo He;Igor Bilogrevic
在本文中，我们研究了使用智能手表运动传感器作为侧信道对手持式数字触摸板进行击键推断攻击的可行性。所提出的攻击方法采用监督学习技术来准确地将捕获的手腕运动的独特性映射到每个单独的击键。实验评估表明，使用智能手表运动传感器的击键推断不仅相当准确，而且优于之前使用智能手机运动传感器演示的类似攻击。
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.