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.
You just measure the time until the delivery recipe arrives. You can approximate how far away the recipient is. Now you keep doing that while changing your own location (use vpns etc.) and you can slowly get a more accurate location of the target. Now you automate that stuff and also utilize machine learning to interpret the data.
This is not possible due to the nature of the exploit. You are required to use a smartphone or similar device that can send SMSes and execute code. SMS traffic is resistant to VPNs, and do not always get sent over the routeable internet path to a local SMSC. Some carriers do operate a little more cleverly than that.
Carriers on the other hand; have a large variety of mitigation techniques at their disposal; including introducing randomized delays into the delivery process of silent SMS types, blocking all delivery of silent SMS types between unauthorized senders, delivering silent SMSes silently without sending receipts that notify the sender it was delivered and many other potential mitigations.