system to recognize features of the acoustic signals associated with each key. They tested the system on the remaining data and found that it could accurately assign the correct key to a sound 95 percent of the time when the recording was made over a phone call and 93% of the time when it was made over a Zoom call.
The study is not the first to show that sound can identify keystrokes, but the team says their study uses the most advanced methods and has achieved the highest accuracy so far. Dr. Ehsan Toreini, who co-authored the study at the University of Surrey, said these attacks and models will be more accurate over time. He also said that as more households use smart devices with microphones, there is a need for public discussions on how to regulate AI. Joshua Harrison, who led the study, said that detecting the release of a shift key is very difficult.