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WristSnoop: Smartphone PINs Prediction Using Smartwatch Motion Sensors

机译:Wristnoop:使用SmartWatch Motion传感器预测智能手机引脚

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Smartwatches, with motion sensors, are becoming a common utility for users. With the increasing popularity of practical wearable computers, and in particular smartwatches, the security risks linked with sensors on board these devices have yet to be fully explored. Recent research literature has demonstrated the capability of using a smartphone's own accelerometer and gyroscope to infer tap locations; this paper expands on this work to demonstrate a method for inferring smartphone PINs through the analysis of smartwatch motion sensors. This study determines the feasibility and accuracy of inferring user keystrokes on a smartphone through a smartwatch worn by the user. Specifically, we show that with malware accessing only the smartwatch's motion sensors, it is possible to recognize user activity and specific numeric keypad entries. In a controlled scenario, we achieve results no less than 41% and up to 92% accurate for PIN prediction within 5 guesses.
机译:具有运动传感器的SmartWatches正在成为用户的常用工具。随着实用可穿戴计算机的普及越来越多,特别是Smartwatches,与电路板上的传感器相关的安全风险尚未完全探索。最近的研究文献已经证明了使用智能手机自己的加速度计和陀螺仪推断点击位置的能力;本文扩展了这项工作,以演示通过智能手表运动传感器的分析推断智能手机引脚的方法。本研究确定了通过用户佩戴的SmartWatch在智能手机上推断用户击键的可行性和准确性。具体而言,我们表明,使用恶意软件仅访问SmartWatch的运动传感器,可以识别用户活动和特定的数字键盘条目。在受控场景中,我们在5次猜测中达到8%,最高可达92%,最高可达92%,高达92%。

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