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Acoustic Snooping on Typed Information Print E-mail
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Source: Freedom To Tinker - Posted by Pax Dickinson   
Security Li Zhuang, Feng Zhou, and Doug Tygar have an interesting new paper showing that if you have an audio recording of somebody typing on an ordinary computer keyboard for fifteen minutes or so, you can figure out everything they typed. The idea is that different keys tend to make slightly different sounds, and although you don’t know in advance which keys make which sounds, you can use machine learning to figure that out, assuming that the person is mostly typing English text. (Presumably it would work for other languages too.)

Asonov and Agrawal had a similar result previously, but they had to assume (unrealistically) that you started out with a recording of the person typing a known training text on the target keyboard. The new method eliminates that requirement, and so appears to be viable in practice.

The algorithm works in three basic stages. First, it isolates the sound of each individual keystroke. Second, it takes all of the recorded keystrokes and puts them into about fifty categories, where the keystrokes within each category sound very similar. Third, it uses fancy machine learning methods to recover the sequence of characters typed, under the assumption that the sequence has the statistical characteristics of English text.

Read this full article at Freedom To Tinker

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