this post was submitted on 30 Jul 2023
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Evangelos Bitsikas, who is pursuing a PhD in cybersecurity at the Northwestern University in the US, applied a new machine-learning program to data gleaned from the SMS system of mobile devices.

Receiving an SMS inevitably generates Delivery Reports whose reception bestows a timing attack vector at the sender. Bitsikas developed an ML model enabling the SMS sender to determine the recipient's location with a 96% accuracy for locations across different countries, the researcher says in a study.

The basic idea is that a hacker would send multiple text messages to the target phone, and the timing of each automated delivery reply creates a fingerprint of the target's location. These fingerprints have ever been there but weren't a problem until Bitsikas' group used ML to develop an algorithm capable of reading them. They can be fed into the machine-learning model, which then responds with the predicted location.

According to the researcher, it doesn't matter whether or not the communication is encrypted.

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[–] TehPers 1 points 1 year ago

If I understand this correctly, isn't this solved by randomly adding delays on the cell towers to these delivery reports? I'm not too familiar with the SMS protocol, but I can't imagine adding a little jitter would hurt much of anything.