this post was submitted on 02 Dec 2023
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Researchers in the UK claim to have translated the sound of laptop keystrokes into their corresponding letters with 95 percent accuracy in some cases.

That 95 percent figure was achieved with nothing but a nearby iPhone. Remote methods are just as dangerous: over Zoom, the accuracy of recorded keystrokes only dropped to 93 percent, while Skype calls were still 91.7 percent accurate.

In other words, this is a side channel attack with considerable accuracy, minimal technical requirements, and a ubiquitous data exfiltration point: Microphones, which are everywhere from our laptops, to our wrists, to the very rooms we work in.

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[–] autotldr@lemmings.world 3 points 11 months ago

This is the best summary I could come up with:


In other words, this is a side channel attack with considerable accuracy, minimal technical requirements, and a ubiquitous data exfiltration point: Microphones, which are everywhere from our laptops, to our wrists, to the very rooms we work in.

To make matters worse, the trio said in their paper that they've achieved what they claim is an accuracy record for acoustic side-channel attacks (ASCA) without relying on a language model.

Luckily in this case it's not power usage, CPU frequencies, blinking lights or RAM buses leaking data unavoidably, but a good old-fashioned problem occurring between the computer and chair that can actually be mitigated somewhat easily.

The researchers note that skilled users able to rely on touch typing are harder to detect accurately, with single-key recognition dropping from 64 to 40 percent at the higher speeds enabled by the technique.

Working among the clacking of phantom keyboards would surely annoy everyone, which is why the researchers suggest only adding the sounds to Skype and Zoom transmissions after they've been recording instead of subjecting employees to real-time noisemakers.

Followup research is now going on into using new sources for recordings, like smart speakers, better keystroke isolation techniques and the addition of a language model to make their acoustic snooping even more effective.


The original article contains 656 words, the summary contains 210 words. Saved 68%. I'm a bot and I'm open source!

[–] Sanctus@lemmy.world 2 points 11 months ago (2 children)

Idk how it works with non-NVIDIA GPUs but get Nvidia Broadcast or an equivalent. Its a life saver.

[–] atocci@kbin.social 2 points 11 months ago (1 children)

It doesn't do a very good job of removing my keyboard noise for some reason, and it makes my voice sound noticably worse 😔

[–] Sanctus@lemmy.world 2 points 11 months ago

Mines perfect, my baby can't even scream in my mic. It gets caught. I don't recall messing with settings, and my GPU is a 2080 TI. Idk, hardware maybe? Theres not much to mess with.

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[–] helenslunch@feddit.nl 2 points 11 months ago (19 children)

Someone explain how this works? Doesn't make much sense to me how that's even possible.

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[–] brlemworld@lemmy.world 1 points 11 months ago

Article doesn't say but I would guess they are testing with words and using that to build context for better accuracy. I imagine if you are typing some random password it would not be as accurate. Also the only password I type nowadays is the one to unlock the computer, everything else is in a password vault.

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