this post was submitted on 06 Aug 2023
483 points (94.1% liked)

Technology

63035 readers
5067 users here now

This is a most excellent place for technology news and articles.

Our Rules

  1. Follow the lemmy.world rules.
  2. Only tech related content.
  3. Be excellent to each other!
  4. Mod approved content bots can post up to 10 articles per day.
  5. Threads asking for personal tech support may be deleted.
  6. Politics threads may be removed.
  7. No memes allowed as posts, OK to post as comments.
  8. Only approved bots from the list below, to ask if your bot can be added please contact us.
  9. Check for duplicates before posting, duplicates may be removed
  10. Accounts 7 days and younger will have their posts automatically removed.

Approved Bots

founded 2 years ago
MODERATORS
L3s
enu
technopagan
L4s
483
New acoustic attack steals data from keystrokes with 95% accuracy (www.bleepingcomputer.com)
submitted 2 years ago by L4s to c/technology
72 comments fedilink hide all child comments
 

New acoustic attack steals data from keystrokes with 95% accuracy::A team of researchers from British universities has trained a deep learning model that can steal data from keyboard keystrokes recorded using a microphone with an accuracy of 95%.

you are viewing a single comment's thread
view the rest of the comments
[–] Coreidan 177 points 2 years ago* (last edited 2 years ago) (17 children)

I’ll believe it when it actually happens. Until then you can’t convince me that an algorithm can tell what letter was typed from hearing the action through a microphone.

This sounds like absolute bullshit to me.

The part that gets me is that the ONLY reason this works is because they first have to use a keylogger to capture the keystrokes of the target, then use that as an input to train the algorithm. If you switch out the target with someone else it no longer works.

This process starts with using a keylogger. The fuck you need “ai” for if you have a keylogger?!? Lol.

[–] egeres 1 points 2 years ago

Is gonna sound crazy, but I think you can skip the keylogger step!

You could make a "keystroke-sound-language-model" (so like a language model that combines various modalities, e.g, flamingo), then train that with self-supervised learning to match "audio" with "text", and have a system where:

  • You listen to your target for a day or so, let's say, 1000 words typed in 🤷🏻‍♂️
  • Then the model could do something akin to anchor tokens in language-to-language translation, except in this case it would be more like fixing on easy words such as "the" to give away part of the sound-to-key map. Then keep running this mapping more parts of the keyboard
  • Eventually you try to extract passwords from your recordings and maybe bingo

I think it's very narrow to think that, just because this research case requires a keylogger, these systems couldn't evolve other time to combine other techniques

load more comments (16 replies)