This is a VERY controlled environment - and they used 20 passes of each person walking with direct knowledge of each person to train for identity. They did no tests with multiple people walking at the same time, or with any other external moving distortion effects (doors opening, etc) . This is very far from actual 'identification' of people in real public settings - and no doubt the cell phone everyone is carrying with them offers many orders of magnitude better opportunity. In a real crowded environment this would be nearly worthless.
The devices that reported BFI information were also stationary, and there were no extra devices transmitting information that would be conflicting.
A single camera would be much more effective.
Yes, but things could be refined. With more resources and research thrown at it, it could become more versatile, that's why the title of the post says "could". And chances are, there are private and government entities already doing this. Research like this has been coming out for at least a decade now.
Even Xfinity has motion detection in homes using this technique now:
Yes, you won't be able to do this on normal wifi traffic typically either, you need to send specific packets at a high enough rate (in between normal internet traffic) in order to sense with any accuracy, as I also remarked earlier: https://news.ycombinator.com/item?id=46976849
Yea, that makes sense as you would need quite a bit of information across a reasonable temporal range if the identifying qualities are movement related. Very interesting.
Exactly. All of these stories using WiFi to detect things with high accuracy are just extreme machine learning demos.
Given a tightly controlled environment and enough training data, you can use a lot of things as sensors.
These techniques are not useful for general purpose sensing, though. The WiFi router in your home isn't useful for this.
This is going into the next Wifi standard specifically to get this data off of normal wifi traffic.
Well nowadays you individually track by using mac addresses and other network information from the devices within range. Cisco has some creepy real time maps of your location with each person walking around and all their previous visits etc
Modern phones connect with a randomized MAC address. So yes, you can track a person around, but you will need another system (like the WiFi login page) to match MAC to identity.
Really? I thought it was only I phones that did that though?
windows 11 also has it.
Not sure how many people are aware that the newer Alexa devices have "presence detection" that uses ultrasound so they can detect when people are nearby. [0]
Heck, even Ecobee remote temperature sensors can do this.
Reminds me of the story about how the Google Nest smoke detector had a microphone in it. [1]
0 - https://www.amazon.com/b?node=23435461011&tag=googhydr-20&hv...
1- https://www.reddit.com/r/privacy/comments/asmusq/google_says...
The Nest smoke detector microphone was never really secret. It was part of the monthly self test to determine if the alarm was working. It would send you a notification telling you it was going to sound the alarm and that it would be listening for the sound to confirm it was working.
It was listed in the features for the 2nd gen units. https://support.google.com/googlenest/answer/9229922#zippy=%...
>newer Alexa devices have "presence detection"
Not even the biggest privacy issue of using Alexa devices. I think listening you 24/7 is a bigger potential issue.
Not sure if Alexa has this, but cheap mm-wave wideband multi-GHz sensors(or radars more accurately) now enable more finely grained human presence detection and also human fall detection[1] with the right algos, so you can for example detect if grandma in the nursing home fell down and didn't get back up, but in a privacy focused way that doesn't resort to microphones or cameras. Neat.
>Reminds me of the story about how the Google Nest smoke detector had a microphone in it.
Vapes have microphone arrays in them to detect when you're sucking and light up the heating element. Cheap electronics have enabled a new world of crazy.
[1] https://www.seeedstudio.com/MR60FDA2-60GHz-mmWave-Sensor-Fal...
Every capacitor can be a potential microphone ...
Android devices already know exactly where they are even with GPS disabled, because they sniff the nearby WIFI networks and then ask Google where they are. QED Google knows already, all combined is mass metadata surveillance already provided to those that tap into it.
Any sub-meter precision or presence detection does not really matter, if these companies have all your other questions, queries, messages, calendars, browse history, app usage, and streaming behaviour as well.
[delayed]
The approach described in the article is much different and more interesting, as it's passive and doesn't require any electronics on the individual being identified.
> The method takes advantage of normal network communication between connected devices and the router. These devices regularly send feedback signals within the network, known as beamforming feedback information (BFI), which are transmitted without encryption and can be read by anyone within range.
> By collecting this data, images of people can be generated from multiple perspectives, allowing individuals to be identified. Once the machine learning model has been trained, the identification process takes only a few seconds.
> In a study with 197 participants, the team could infer the identity of persons with almost 100% accuracy – independently of the perspective or their gait.
So what's the resolution of these images, and what's visible/invisible to them? Does it pick up your clothes? Your flesh? Or mosty your bones?
What happens is that a large body of water (pun intended) has the ability to absorb and reflect wifi signals as it moves through the room. For this you need to generate traffic and measure for instance RSSI or CSI (basically, signal strength) of the packets. If you increase frequency you can detect smaller movements such as arms moving vs. a body, or exclude pets if you reduce sensitivity. It works well for detecting presence and movement in a defined space, but ideally requires you to cross the path between two mains-powered devices, such as light bulbs or wifi mesh points. Passing a cafe doesn't seem too likely.
If you want to do advanced sensing, trying to identify a person, I would postulate you need to saturate a space with high frequency wifi traffic, ideally placed mesh points, and let the algo train on identifying people first by a certain signature (combination of size/weight, movement/gait, breath / chest movements).
Source: I worked on such technologies while at Signify (variants of this power Philips/Wiz "SpaceSense" feature).
More here: https://www.theverge.com/2022/9/16/23355255/signify-wiz-spac...
> So what's the resolution of these images, and what's visible/invisible to them?
The researchers never claimed to generate "images," that's editorializing by this publication. The pipeline just generates a confidence value for correlating one capture from the same sensor setup with another.
[Sidenote: did ACM really go "Open Access" but gate PDF download behind the paid tier? Or is the download link just very well hidden in their crappy PDF viewer?]
Resolution and positional accuracy are very poor. It’s more like ‘an approximate bag of water detector’.
Gait analysis is complete fiction. Especially with a non-visual approach like this.
Given the number of gait analysis publications over several decades using varying techniques, can you recommend a good review article disproving all of them?
If you can do that you can infer when someone is home or away.
From the paper linked by jbotz
> The results for CSI can also be found in Figure 3. We find that we can identify individuals based on their normal walking style using CSI with high accuracy, here 82.4% ± 0.62.
If you're a person of interest you could be monitored, your walking pattern internalized in the model then followed through buildings. That's my intuition at practical applications, and the level of detail.
They tested correlation between different perspectives (same scene and AP even) later in the paper and achieved an accuracy of 0%. Not to discount other methods being able to achieve that.
It's at least possible to record heart rate with wifi, so that suggests a broad variety of biometrics can be recorded.
Various cheating to get their conclusions (from the paper):
> To allow for an unobstructed gait recording, participants were instructed not to wear any baggy clothes, skirts, dresses or heeled shoes.
> Due to technical unreliabiltities, not all recordings resulted in usable data. For our experiments, we use 170 and 161 participants for CSI and BFI, respectively. [out of 197]
I wish they had explained what the technical unreliabilities were.
You can do it to yourself[1], I am using Tommy for presence detection in Home Assistant, works great (my house is small, so two ESP32s works fine, I am sure having 3-4 would let it see my cat breathing).
Cameras just use light waves and are already a mass surveillance system.
Beamforming information is utilized for creating this surveillance. There are also a lack of configurations in common routers to turn off BFI. The BFI information is available to any WiFi snooping and can easily be used to detect presence. You just need to read the BFI data (its plaintext) and if it changes, you can track wherever the smartphone the beam is now pointing towards. Detecting exactly who is another feature but in general, WiFi technologies are insecure and easily available as surveillance devices.
I don't feel that this article is a fair summary of the paper. And the title is just clickbait.
The paper says, in a somewhat contrived scenario, with dozens of labelled walkthroughs per person, they can identify that person from their gait based on CSI and other WiFi information.
This is a long way from identifying one person in thousands or tens of thousands, being able to transfer identifying patterns among stations (the inference model is not usable with any other setup), etc.
All the talk of "images" and "perspectives" is journalistic fluffery. 2.4Ghz and 5Ghz wavelengths (12cm & 6cm) are too long to make anything a layperson call an "image" of a person.
What creepy thing could you actually do with this? Well, your neighbor could probably record this information and tell how many and which people are in your home, assuming that there is enough walking to do a gait analysis. They might be able to say with some certainty if someone new comes home.
That same neighbor could hide a camera and photograph your door, or sniff your WiFi and see what devices are active or run an IMSI catcher and surveil the entire neighborhood or join a corporate surveillance outfit like Ring. Using the CSI on your WiFi and a trained ML model is mostly cryptonerd imaginiation.
Indeed. I'm confused by this line from the article
> a study with 197 participants, the team could infer the identity of persons with almost 100% accuracy – independently of the perspective or their gait.
The paper seems to make it clear that the technique still depends on gait analysis, but claims it's more robust against gait variations.
The paper also makes clear they had no success correlating across different perspectives- welcome to science reporting.
It feels rather more than a little bit creepy to realize that Comcast et al, and thus the US government (if you live there), laundered through 3rd party data brokers, knows if you're sleeping and knows if you're awake. Knows if you've been bad or good, for ICE/ATF/DEA/SEC's sake.
Comcast is late to the party, then. AT&T has been selling your information for decades. And your mobile provider can track you anyplace that there's a cell-signal, potentially even outside the country.
no, dumbass this has been done for decades.
It's known as your "hand"
So, should I start walking around with a jammer or something?
What about rotating MAC address?
Reminds me of the xfinity in-home wifi motion detection, discussed here: https://news.ycombinator.com/item?id=44426726
I don't see how this is categorically any different from hidden networked cameras. Perhaps that's the real issue we should be focusing on in terms of privacy and mass surveillance.
Scary title, 3 month late into the party… really we don’t deserve better articles with non-dramatic content, much faster?
> In a study with 197 participants, the team could infer the identity of persons with almost 100% accuracy
That a super impressive! I wonder how that would be at scale, with a few millions people. I’m don’t think that would remain as accurate
Could this be countered by wearing wire-mesh patch clothing, perhaps in randomized stylish arrangements?
Probably. If you look at the paper they wouldn't let their participants wear loose or baggy clothing.
No! That would make you stand out with the fiery intensity of a sun.
If the metal bits are floppy enough it should add quite a bit of noise
How about personal canisters of chaff that get fired off whenever I enter a room? Before long, folks will get so annoyed with all of the metal fibers I leave behind, that I simply won’t be invited anywhere and my anonymity will have been protected.
Perhaps we should ask be using aluminium foil hat now
LOL @ "Could"
Nothing says "out of touch with reality" like 'murcan media.
I’m not understanding this. You still have to deploy a piece of hardware to read the Wi-Fi waves. Why wouldn’t you just deploy some other piece of hardware that’s better at surveilling the surroundings? Also, if the Wi-Fi device is in the area are not busy now your camera is off that doesn’t seem good. Also, I imagine you have to tune it for every environment, geometry that doesn’t sound easy. And then after all that work, I move my Wi-Fi router 4 inches to the left.
I’m not understanding this. You still have to deploy a piece of hardware to read the Wi-Fi waves. Why wouldn’t you just deploy some other piece of hardware that’s better at surveilling the surroundings? Also, if the Wi-Fi device is in the area are not busy now your camera is off that doesn’t seem good. Also, I imagine you have to tune it for every environment, geometry that doesn’t sound easy.
I’m not understanding this. You still have to deploy a piece of hardware to read the Wi-Fi waves. Why wouldn’t you just deploy some other piece of hardware that’s better at surveilling the surroundings? Also, if the Wi-Fi device is in the area are not busy now your camera is off that doesn’t seem good
I’m not understanding this. You still have to deploy a piece of hardware to read the Wi-Fi waves. Why wouldn’t you just deploy some other piece of hardware that’s better at surveilling the surroundings?
There is no could. This is a turnkey function for any modern managed wifi system right now.
“Could become”
Already is and widely used for exactly what the article worries about
Can you say what products make use of this technique? i.e. is it well known like Juniper Mist or not publicly available?
Verizon has a security feature built around this, https://www.xfinity.com/hub/smart-home/wifi-motion
Philips WiZ bulbs: https://www.wizconnected.com/en-us/explore-wiz/spacesense
Alarm.com also supports such sensors: https://poweredbyalarm.com/eventresources/wp-content/uploads...
There's a big difference between 'presence detection' and 'tracking individuals'. Both in terms of tech and privacy impact.
Source?
This reads like proper science fiction tech!
Can we make WiFi 2 that doesn’t let people do this?
Microwave frequencies like 2.4 or 5 GHz just passively allow you to do this. You'd have to adopt frequencies that are useless for radar.
I mean you could even jam a microwave oven door open, turn it on, and then measure how much energy loss there was through certain paths. That's essentially all beamforming in Wifi requires -- a really sophisticated way of measuring paths that cause energy loss, and a really sophisticated antenna design that allows you to direct the signal through paths that don't cause energy loss. The first problem is what's facilitating surveillance because humans cause signal loss because our bodies are mostly water, and 2.4 GHz radio waves happen to get absorbed really well by water. This causes measurable signal loss on those paths and the beamforming antennae use that information to route around your body. But they could also just log that information and know where you are relative to the WAP.
Not surprised, related: https://news.ycombinator.com/item?id=46920315
That's more than related