iSpy: automatic reconstruction of typed input from compromising reflections
iSpy: automatic reconstruction of typed input from compromising reflections
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DOI：
10.1145/2046707.2046769
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发表时间：
2011-10
期刊：
影响因子：
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通讯作者：
R. Raguram;A. M. White;D. Goswami;F. Monrose;Jan-Michael Frahm
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文献类型：
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作者：
R. Raguram;A. M. White;D. Goswami;F. Monrose;Jan-Michael Frahm
我们调查了个人移动设备无处不在的影响，并揭示了损害用户在虚拟键盘上打字隐私的新技术。具体来说，我们展示了设备屏幕上所谓的折衷反射（例如，在受害者的太阳镜中）足以实现从视频中自动重建在虚拟键盘上输入的文本。尽管我们故意使用低成本的商用摄像机，但我们能够通过应用先进的计算机视觉和机器学习技术来补偿诸如任意摄像机和设备定位和运动等变量。使用在现实环境中捕获的片段（例如，在公共汽车上），我们表明我们能够在几乎所有的测试用例中重建记录数据的流畅翻译，同时纠正用户的输入错误。我们认为，这些结果突出了调整隐私预期以应对新兴技术的重要性。
We investigate the implications of the ubiquity of personal mobile devices and reveal new techniques for compromising the privacy of users typing on virtual keyboards. Specifi- cally, we show that so-called compromising reflections (in, for example, a victim's sunglasses) of a device's screen are sufficient to enable automated reconstruction, from video, of text typed on a virtual keyboard. Despite our deliberate use of low cost commodity video cameras, we are able to compensate for variables such as arbitrary camera and device positioning and motion through the application of advanced computer vision and machine learning techniques. Using footage captured in realistic environments (e.g., on a bus), we show that we are able to reconstruct fluent translations of recorded data in almost all of the test cases, correcting users' typing mistakes at the same time. We believe these results highlight the importance of adjusting privacy expectations in response to emerging technologies.