The Peeping Eye in the Sky
The Peeping Eye in the Sky
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DOI：
10.1109/glocom.2018.8647787
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发表时间：
2018-12
期刊：
影响因子：
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通讯作者：
Qinggang Yue;Zupei Li;Chao Gao;Wei Yu;Xinwen Fu;Wei Zhao
中科院分区：
文献类型：
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作者：
Qinggang Yue;Zupei Li;Chao Gao;Wei Yu;Xinwen Fu;Wei Zhao
在本文中，我们调查了配备有记录设备的无人机的威胁，记录设备捕获个人在其移动的设备上打字的视频，并从视频中提取触摸输入，如密码。从空中部署这种攻击具有很大的挑战性，因为无人机动力学和风引起的相机振动和移动。我们的演算法可以估计出手指的运动轨迹，并推导出打字模式，进而得到触控输入。我们的实验表明，我们可以在远距离使用DJI Phantom无人机对抗平板电脑和智能手机时实现高成功率。一架2.5英寸的NEUTRON迷你无人机在窗外飞行，也实现了对窗后平板电脑的高成功率。据我们所知，我们是第一个系统地研究无人机揭示移动的设备上的用户输入，并单独使用手指运动轨迹来恢复在移动的设备上键入的密码的人。
In this paper, we investigate the threat of drones equipped with recording devices, which capture videos of individuals typing on their mobile devices and extract the touch input such as passcodes from the videos. Deploying this kind of attack from the air is significantly challenging because of camera vibration and movement caused by drone dynamics and the wind. Our algorithms can estimate the motion trajectory of the touching finger, and derive the typing pattern and then touch inputs. Our experiments show that we can achieve a high success rate against both tablets and smartphones with a DJI Phantom drone from a long distance. A 2.5" NEUTRON mini drone flies outside a window and also achieves a high success rate against tablets behind the window. To the best of our knowledge, we are the first to systematically study drones revealing user inputs on mobile devices and use the finger motion trajectory alone to recover passcodes typed on mobile devices.