Researchers at IMDEA Networks Institute, together with European partners, have found that tire pressure sensors in modern cars can unintentionally expose drivers to tracking. Over a ten-week study, they collected signals from more than 20,000 vehicles, revealing a hidden privacy risk and highlighting the need for stronger security measures in future vehicle sensor systems. Most...
Yeah, I don’t know what the range is for picking these signals up, but I know that the detections just scroll on and on on my laptop’s screen when there is any traffic near my house.
I never realized how chatty the world is on the radio spectrum until playing with one of these. From my house, I can see reports from half a dozen water meters (several reporting leaks), readings from wireless weather stations, signals from certain types of remotes, location data from aircraft, and of course bluetooth and wifi signals from phones and homes. The real trick in using this for tracking would be in filtering out all of the information you aren’t interested in.
Yes and no, I think. It isn’t really huge amounts of data, and the patterns aren’t super complex, so a neural network would pick up a lot. But, given how far the signals travel, the intermittent nature of the signals, and how little they can initially be associated with a particular vehicle, I think in most environments associating a particular set of signals with a particular car would require some human field work. Sure, there are circumstances where automated pairing would be trivial (like at a toll booth), but catching signals in the wild and processing by neural net alone might be ok for analyzing traffic patterns while not being enough for surveillance.
Yeah, I don’t know what the range is for picking these signals up, but I know that the detections just scroll on and on on my laptop’s screen when there is any traffic near my house.
I never realized how chatty the world is on the radio spectrum until playing with one of these. From my house, I can see reports from half a dozen water meters (several reporting leaks), readings from wireless weather stations, signals from certain types of remotes, location data from aircraft, and of course bluetooth and wifi signals from phones and homes. The real trick in using this for tracking would be in filtering out all of the information you aren’t interested in.
Yeah this is something a well trained neural network would make simple though. So long as you have the processing power, and enough storage.
I’d imagine you’d be able to purchase some identifying information from data brokers and eventually link ids to people or families.
Yes and no, I think. It isn’t really huge amounts of data, and the patterns aren’t super complex, so a neural network would pick up a lot. But, given how far the signals travel, the intermittent nature of the signals, and how little they can initially be associated with a particular vehicle, I think in most environments associating a particular set of signals with a particular car would require some human field work. Sure, there are circumstances where automated pairing would be trivial (like at a toll booth), but catching signals in the wild and processing by neural net alone might be ok for analyzing traffic patterns while not being enough for surveillance.