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Attacks against emanations caused by human typing have attracted interest in recent years. In particular, works showed that keyboard acoustic emanations do leak information that can be exploited to reconstruct the typed text.<ref name="[Ber1]">[[#Ber1|Berger, 2006, p.1]]</ref>
PC keyboards, notebook keyboards are vulnerable to attacks based on differentiating the sound emanated by different keys.<ref name="[Aso1]">[[#Aso1|Asonov, 2004, p.1]]</ref> This attack takes as input an audio signal containing a recording of a single word typed by a single person on a keyboard, and a dictionary of words. It is assumed that the typed word is present in the dictionary. The aim of the attack is to reconstruct the original word from the signal.<ref name="[Ber2]">[[#Ber1|Berger, 2006, p.2]]</ref> This 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.<ref name="[Zhu1]">[[#Zhu1|Zhuang, 2005, p.1]]</ref> This attack is inexpensive because the other hardware required is a parabolic microphone and non-invasive because it does not require physical intrusion into the system. The attack employs a neural network to recognize the key being pressed.<ref name="[Aso1]">[[#Aso1]]</ref> It combines signal processing and efficient data structures and algorithms, to successfully reconstruct single words of 7-13 characters from a recording of the clicks made when typing them on a keyboard.<ref name="[Ber1]"
On average, there were only 0.5 incorrect recognitions per 20 clicks, which shows the exposure of keyboard to the eavesdropping using this attack.<ref name="[Aso2]">[[#Aso1|Asonov, 2004, p.4]]</ref>
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