zlacker

[return to "New acoustic attack steals data from keystrokes with 95% accuracy"]
1. lispis+Pq[view] [source] 2023-08-05 19:14:25
>>mikece+(OP)
So they generated training data from one laptop and microphone then generated test data with the exact same laptop and microphone in the same setup, possibly one person pressing the keys too. For the Zoom model they trained a new model with data gathered from Zoom. They call it a practical side channel attack but they didnt do anything to see if this approach could generalize at all
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2. OtherS+zA[view] [source] 2023-08-05 20:24:31
>>lispis+Pq
I believe that is the generalisable version of the attack. You're not looking to learn the sound of arbitrary keyboards with this attack, rather you're looking to learn the sound of specific targets.

For example, a Twitch streamer enters responses into their stream-chat with a live mic. Later, the streamer enters their Twitch password. Someone employing this technique could reasonably be able to learn the audio from the first scenario, and apply the findings in the second scenario.

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3. yowzad+FB[view] [source] 2023-08-05 20:32:53
>>OtherS+zA
I guess more reason to just use a password manager to autofill your password?
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4. kypro+HC[view] [source] 2023-08-05 20:41:31
>>yowzad+FB
Or just use 2fa
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5. barrot+A51[view] [source] 2023-08-06 01:01:50
>>kypro+HC
Now that I know about the existence of this generation of acoustic attacks I would like to have the possibility to insert a second "master password" different from the main one, that instead of letting me directly access to my passwords just allows me to use fingerprint to get them. Guess if it's already possible
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