Snooping on Text by Listening to the Keyboard
http://www.cs.berkeley.edu/~tygar/papers/Keyboard_Acoustic_Emanations_Revisited/preprint.pdf
We examine the problem of keyboard acoustic emanations. We present a novel attack taking as input a 10-minute sound recording of a user typing English text using a keyboard, and then recovering up to 96% of typed characters. There is no need for a labeled training recording. Moreover the recognizer bootstrapped this way can even recognize random text such as passwords: In our experiments, 90% of 5-character random passwords using only letters can be generated in fewer than 20 attempts by an adversary; 80% of 10-character passwords can be generated in fewer than 75 attempts. Our attack uses the statistical constraints of the underlying content, English language, to reconstruct text from sound recordings without any labeled training data. The attack uses a combinationof standard machine learning and speech recognition techniques,including cepstrum features, Hidden Markov Models, linear classification, and feedback-based incremental learning.
Peccato, a me le vecchie tastiere rumorose, nel quale si sentiva la pressione del tasto, mi piacevano parecchio! comunque ... sssshh, da domani fate piano, tutti a battere dolcemente sulle tastiere :)
