And it can do it with a startling 93 percent accuracy.
, a UK-based team of researchers emphasizes the modern ubiquity of microphone-equipped personal devices, which has, in turn, given rise to a new wave of audio-targeted cyberattacks; add "recent developments in deep learning" to the mix, they say, and you have a dangerous cybersecurity cocktail that could leave sensitive information like passwords exposed to savvy bad actors.
The training process for the "classifier," as the model is referred to in the paper, was also surprisingly simple. The researchers pressed 36 keys on the Macbook Pro a total of 25 times each, recording the keystrokes on two different mediums: a nearby iPhone's microphone and Zoom audio. The program learned from there, and later, when tested on each medium, the classifier achieved respective reading accuracies of 95 and 93 percent. When compared to
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