Researchers Issue Warning About Tech That Could Turn Every Router 'Into a Potential Means for Surveillance'
gizmodo.com
Researchers warn that a new method for detecting people through WiFi signals poses a serious privacy risk.

The technology to convert wifi signals into the placement and identity of people is getting much better. Not by using their devices, just the waves bouncing of their bodies. (There’s nothing new to the pipeline as far as I can tell, we’re just starting to get into the accuracy ranges that make it easy/useful.)

  • Artisian@lemmy.worldOPEnglish
    1·
    6 hours ago

    Thank you. I could be persuaded to change the title, though I don’t think I have been. (You are perhaps not trying to, but I’ll record my reasoning anyway.)

    Re: nobody is motivated to do this. True, and doesn’t contradict the title or content. Anybody could drive out and start toppling power poles and poisoning the water supply, fortunately most people are mostly good.

    Re: some houses are well insulated. Congrats on your nice home! Many dream of having their own space someday. I think the most interesting case is in an apartment/condo/high density complex. In this setting, you have:

    • the layout of the entire building, including other rooms. (modulo furniture and dustables; the walls are public.)
    • many routers all over the building, overlapping and generally at different frequencies. When I AirBnB, I often see dozens of different networks from my bedroom. Note that for this style of attack, you don’t need to connect to anything.
    • thin walls between units (often cheap).
    • some incentive towards snooping. Who stole your packages? Which neighbor keeps letting the dog poop at your window?

    Re: training required and the field of view This I find most compelling. I am interested in how much legitimate use is required; can we simply make login attempts? Or does it take somebody logged in? It’s hard for me to tell how customized the model must be (this is a setting where data is reasonably easy to generate in a lot of settings; perhaps enough so that, given a model slightly larger, we get something general?).