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.
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:
like i mentioned in another comment, do you really need good resolution for gait analysis? You also have people carrying their phones inside the house all the time, so you know what bssid is associated with that coarse movement. and if you have access to their ap/router combo, you can tell what IP that device has and what domains it's been visiting.
Let's say you visit a friend in a different city, the same ISP controlling their router, can use your mac, but even if you turn off your wifi or leave your phone in your car, your volume profile and gait can betray you. how you sit, how you lean, how you turn. I'd wager, if 6-10 distinct "points" can be made out and associated with a person, that's all that's needed to uniquely identify that person after enough analysis of their motion, regardless of where they go in the world.
Imagine if they're not using one AP, but using your neighbors AP as well, two neighbor APs and your own can triangulate and refine much better.
This has already been an area of research, both publicly, and most likely in private/government defense research. In a targeted situation, i.e. surveillance of a household of 6, this would work easily enough...but I doubt there is enough information to provide reliable (high AUC) tagging of ID in a public scenario oh hundreds to thousands of individuals.
> Researchers in Italy have developed a way to create a biometric identifier for people based on the way the human body interferes with Wi-Fi signal propagation.. can re-identify a person in other locations most of the time when a Wi-Fi signal can be measured. Observers could therefore track a person as they pass through signals sent by different Wi-Fi networks – even if they’re not carrying a phone.. their technique makes accurate matches on the public NTU-Fi dataset up to 95.5 percent.
if it's a public scenario, you don't need that, they're using wifi on people's persons to id them. The concern is more gait analysis, and by some accounts even lip reading is possible with mm-wave 5g.
> Even Xfinity has motion detection in homes using this technique now
WiFi presence detection is a completely different problem. If the WiFi environment is changing past a threshold, return a boolean yes or no. It can't actually tell if someone is present or if the environment is just changing, such as a car driving close enough to reflect signals back in a certain way.
Doing mass surveillance where you detect individual people in a random home environment isn't the same thing at all. All of these "could" claims are trying to drawn connections between very different problems.
You'll have to explain that a bit more. Isn't the threshold detection analyzing radio signal data? For identifying people, you don't need to reconstruct their face or fingerpring using that data. you just need to fingerprint them.
With gait analysis for example, it's only looking at a handful of data points, the way we walk is very unique. lip-reading, i can see how that's a stretch, but out movement patterns and gait are disturbances in radio waves. If you're using just one person's wifi, that sounds difficult, but if you're collecting signal from multiple adjacent wifi access points, it's more realistic to build a very coarse motion representation, perhaps with a resolution no finer than 1 cubic ft, but even with more coarse representations, gait can be observed.
Even gait aside, the volume profile of a person and their location in the house alone are important data points, couple that with the unique wifi identifier or IP, you can make a really good guess at who the person is, and what room they're in.
Only if wifi is radically increased in frequency, power, directionality or antenna size. And i mean way beyond practicallity. It would be easier to identify people by the sounds of thier footsteps, something easily done through anything with a microphone. With three microphones, you can track that movement to the inch.
the article is off-base with wifi. the real story is in 6G cellular.
there is a working group at 3gpp, an EU-funded research group (6th sense, Open6GHub), universities (NCSU, Bristol), and many companies working very hard right now on proposals to include "integrated/joint sensing and communication" (ISAC/JCAS) in the 6G spec.
ISAC means adding mmWave to 6G (ostensibly for speed, but also) to build a high-fidelity 3d realtime "digital twin" of the real world that can see through walls, owned and operated by your telecom provider.
> A very exciting innovation that 6G will bring to the table would be its ability to sense the environment. The ubiquitous network becomes a source of situational awareness, collating signals that are bouncing off objects and determining type and shape, relative location, velocity and perhaps even material properties. With adequate 6G solutions for privacy and trust, such a mode of sensing can help create a “mirror” or digital twin of the physical world in combination with other sensing modalities.
there's been a testbed deployment in a German hospital for "non-invasive" monitoring of vitals; which sounds to me like it can literally see a heartbeat.
truth is, this is the nature of wireless radios. we can't keep improving bandwidth and latency without also turning the radio into a camera. i'm disturbed by the inevitability.
> ISAC means adding mmWave to 6G (ostensibly for speed, but also) to build a high-fidelity 3d realtime "digital twin" of the real world that can see through walls, owned and operated by your telecom provider.
"See through walls"
There used to be a great video on youtube of a very high power 60GHz signal being blocked by a door. Sad I can never find it. E Band isn't much better.
IIRC the 60GHz radio is being left out of a lot of 5G deployments because the slight benefits don't outweigh the cost.
This is a pretty common thing for mmWave (or near mmWave) to be deployed with massive fanfare and then be slowly phased out of existence. I am decidedly not writing this on a WiGig docking station.
I dont see telcos wanting to constantly broadcast extra mmWave for little to no added benefit, especially not in all directions. Likewise, regulators are going to choke on that. And the class/band license schemes would have to be updated, to remove interference from devices already using those bands as they are about to have a constant background level of interference. E-Band PTP users, of which there are many, wont give up their high capacity links to weird 6G omni broadcasts without a fight.
I tell you what however, having a button you can press that would map the environment for alignment sounds like a maybe use case here. Better than a camera for detecting new obstructions when links go down.
They might also add more bands to the whole automatic MIMO backhaul trick they have been pursuing.
They can do that by looking at the cars in my driveway/garage and or just watching the windows for any period of time. Plus my phone. If <insert 3 letter agency> agents are sitting outside of your house, they aren't going to drive away because you pull the plug on the router and suddenly deprive them of BFI packets.
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.
There'll be an update where a first responder can send a special packet to an SSID that will enable these high rate packets without needing to join the wifi. It'll be secure where only the good guys will know about it so that it won't be able to be used nefariously. /s
WiFi AP's already do a lot of tracking and measurement just to improve signal fidelity and effective throughput. Why wouldn't those same techniques be useful for more general object tracking? Of course using a single AP to attempt to track movement in real-time is unlikely to have great results, but with several APs and enough compute triangulation should improve results.
> Why wouldn't those same techniques be useful for more general object tracking?
These demos use machine learning to train against a known environment.
Basically, pattern matching changes in the signals against a very controlled set of training data.
You can use WiFi signals to detect that something is changing in the environment, but without the machine learning with controlled input data you don't know what it actually means. This is how WiFi presence detection works, but it won't tell you if it's a person moving through the house or your cat walked in front of the router.
If I was interested in mass surveillance I would combine the radio data (WLAN, BT, ...) with the camera feed. If you then see the same person with ML, you can correlate that with radio's. You can even do that with cell towers with anonymous SIM, especially if combined with public transport camera feed or ALPR/ANPR.
HEADLINE: Electromagnetic radiation can be used to see!!!!
Right, that's what your eyes do. Radio is much longer wavelength than visible light (~5-10cm). So at best it offers extremely crappy resolution unless - you're doing something clever with second order information.
Yes it's in a controlled environment not in a real world noisy environment.
But this is more stealthy than a camera and could potentially work with non-line-of-sight or even through walls.
And based on that I could imagine with a combination of a camera and this method, you could train the model on data where both the camera and this method is seeing the individual and then continue to track them with the wifi sensing + the trained model even where the camera cannot see them anymore.
But yea real world is noisy, so it could be very challenging.
Yeah I've seen this same type of study done over the years with the same dire warning. But like you pointed out it's just extremely labor intensive when it's simply easier to attack phones, security cameras or any other smart device that can be easily hacked. Or just install your own bugs.
Would not be surprised to see this get more traction right now due to the political climate.
Yeah this is one of those "cool demo" research results that is completely impractical in the real world that is sold (probably by university PR departments) as an actual viable technique that might have real-world implications.
We've seen it before with things like taking photos around corners.
And no, it isn't like the Wright flyer and a bit crap now but in 40 years we have jet planes. This will never get significantly better.
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.
In a dynamically changing environment (from the perspective of Wi-Fi signal), this will be difficult but not impossible with modern applications of ML algorithms. We worked on this technique back in 2016-18 at the University of Toronto WIRLab; take a look at the results video from back then. I think the person is somewhat identifiable. https://www.youtube.com/watch?v=lTOUBUhC0Cg
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]
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.
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.
How many people have Alexa devices vs wifi? I got gifted an Amazon Echo Dot some years ago. We set it up and switched it off later the same day because it felt creepy to have the thing listening to everything we said.
with a high speed camera any vibrating reflective object like a potato chips bag can become a weak microphone if you have line of sight even behind a soundproof window:
https://www.youtube.com/watch?v=FKXOucXB4a8
> 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).
You are confusing it with the earlier methods. This is similar but not the same method that doesn't use RSSI or CSI and it is passive.
This approach relies solely on the "unencrypted parts of legitimate traffic".
The attacker does not need to send any packets or "generate" their own traffic; they simply "listen" to the natural communication between an access point and its clients.
BFI is much more complex than simple signal strength. RSSI is an aggregation of information that the researchers describe as "not robust" for fine-grained tasks
In contrast, BFI is a high-resolution, compressed representation of signal characteristics.
This rich data allows the system to distinguish between 197 different individuals with 99.5% accuracy, something impossible with basic RSSI.
While older CSI methods often focused on walking directly between a specific transmitter and receiver (Line-of-Sight), BFI allows a single malicious node to capture "every perspective" between the router and all its legitimate clients.
Also CSI requires specialized hardware and custom firmware, this one isn't, just wifi module in monitor mode.
Given the number of gait analysis publications over several decades using varying techniques, can you recommend a good review article disproving all of them?
Given the number of publications about curing <pick your uncured disease> over several decades using varying techniques, can you recommend a good review article disproving all of them?
Answer: no need, if it had been cured, it would be cured. And it is not.
My point being that many publications saying "towards X" may mean that we are making some progress towards X, but they don't mean at all that X is possible.
I don’t think anyone has ever tried to publish something disproving all of the gait analysis claims. That would be an odd sort of thing. But I have not seen anything come to something that we could call productized and reliable. It’s relatively easy to publish theoretical papers. Much harder to show it working reliably in the wild.
> 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.
> 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?]
The first iPad did not have GPS module. It has location system, though. It worked by listening to WiFi and knowing the location of the routers. The list of them updated over the air.
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.
First this is not just Android. Apple does the same thing. You can buy an iPad which physically does not have any GPS hardware and it can reasonably tell you where you are. Personally I first learned of this feature when I bought a second-generation iPad, so it’s been there a while ago.
Second, it is a logical leap to assume Google knows everything already. They could for example build this nearby Wi-Fi based location querying API with privacy in mind, by purposefully making it anonymous without associating it with your account, going through relays (such as Oblivious HTTP), use various private set intersection techniques instead. It is tired and lazy to argue that just because some Big Tech has the capability of doing something bad therefore they must already be doing it.
> Second, it is a logical leap to assume Google knows everything already. They could for example build this nearby Wi-Fi based location querying API with privacy in mind
In which world are you living?
> It is tired and lazy to argue that just because some Big Tech has the capability of doing something bad therefore they must already be doing it.
It has the capability of doing something bad, and it has a history of doing it. Better not forget the last part.
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.
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.
This "could become" sounds exactly like when you look at a cool robotics project, and when you ask the researcher what it could be used for, they say "it could be used for search & rescue after a natural disaster".
The truth is that it's cool research that currently has zero use-case. But a) journalists would not write about that and b) researchers may try to use examples to explain what their research does. Probably researchers are tempted to find a cool use-case of course, because it's better for them if journalists write about their research.
This sounds like cool research that is not remotely close to becoming an invisible mass surveillance system.
Thanks to this disaster of a website that prompts my browser to accept notifications, and autoplays a video ad that hijacked my audio output and shifted the content I was listening to over to the internal computer speaker.
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.
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.
WiFi Could Become an Invisible Mass Surveillance System
Highly unlikely and would be a waste of effort and resources. In the real world we are already well surveilled by cameras, microphones, satellites, cell phones, televisions, modern vehicles with a large number of cameras, web enabled doorbell cameras, refrigerators, AirTags, robot vacuum cleaners that map our home and monitor us, anything bluetooth enabled and that is even before actual spy devices like laser microphones that can turn most windows into a giant microphone.
All of these methods are far more attainable without trying to recreate microwave imaging that has been used by the feds for ages and the feds use a handheld device vs. this complex lab setup and this is even before we talk about advanced high resolution milspec FLIR which some companies have managed to get into serious trouble for selling to sanctioned countries for ITAR violations.
This reminds me of those side channel attacks in crypto. Maybe it works, but any adversary most certainly has easier ways of surveilling you, like hidden cameras with facial recognition.
I was really impressed that a ESP32 Antenna Array Can essentially make a WiFi camera - it uses both time and phase differences to localize based on MAC addresses (which are sent plaintext) https://www.youtube.com/watch?v=sXwDrcd1t-E
That makes sense. Wi-Fi uses radio waves, part of the light spectrum. Like our eyes or cameras can watch and record, Wi-Fi can also be used for this purpose.
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).
Correct me if I'm wrong but assuming they didn't already know your identity, wearing a mask for instance would prevent profiling you based on your radio wave constructed facial features.
WiFi is already part of invisible mass surveillance systems, though not in the way described in the article. It's part of how cell phones fix location, based on nearby wifi endpoints, which is then sent to google, apple, every app, every advertiser, etc.
WiFi Sensing is part of Wi-Fi 7 and present in most recent laptops and smartphones. Local NPU machine learning can be combined with WiFI radar. Malware can attack phone and radio basebands and exploit this capability. It can uniquely fingerprint human biometrics, measure breathing rate, record keystrokes and more. Thousands of academic papers have been published in the last 15 years on "device free wireless sensing", before the capability was ratified by IEEE as 802.11bf. It's being rolled out commercially. Mitigations include drywall or insulation with a layer of RF shielding.
> Researchers.. developed.. a biometric identifier for people based on the way the human body interferes with Wi-Fi signal propagation.. CSI in the context of Wi-Fi devices refers to information about the amplitude and phase of electromagnetic transmissions.. interact with the human body in a way that results in person-specific distortions.. processed by a deep neural network, the result is a unique data signature.. [for] signal-based Re-ID systems
Caveat: Indoors. However, since indoors is typically a private space, the degree of surveillance depends on the owner of the space. Civilians can only compel government agencies to make sure that government buildings do not enable tracking. We won't be able to stop Walmart, they can always play the security card which trumps privacy every time.
Cool spooky concept, but seems like this could be easily foiled by shoving some aluminum foil into one's pockets or wearing thermal clothing in the winter. Or moving furniture around.
My cheapo Amazon desk is steel framed, and the monitors have all sorts of metal and signals running through them. I know it impacts wifi because my wifi-connected printer gets crappy signal on one side and decent signal on the other. Good luck getting a positive ID via wifi when I'm sitting at it.
Likewise I don't see how this survives in the real world for a mass surveillance application. Any "signature" will be in constant flux as environments change, in terms of everything from crowds to weather. I'll need to see a demo outside of a controlled environment before I start trying to obfuscate my signature or remodel my house to run Ethernet everywhere.
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.
I used the regular home power stuff many years ago and the speeds were pretty bad and the network loss was unreliable.
My understanding is that it has improved in some circumstances, but if the connection ends up "hopping" through your breaker you get back to garbage speeds.
In theory you can get 2 Gbps speeds, but in practice it seems like still around 500 Mbps. I don't know if the loss has improved but it was a significant problem before, since even a low loss will render a connection unusable.
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.
Task Group bf is expected to develop an amendment that defines modifications to the IEEE 802.11 medium access control layer (MAC) and to the Directional Multi Gigabit (DMG) and enhanced DMG (EDMG) PHYs to enhance Wireless Local Area Network (WLAN) sensing (SENS) operation in license-exempt frequency bands between 1 GHz and 7.125 GHz and above 45 GHz.
---
- Stations to inform other stations of their WLAN sensing capabilities
- Request and setup transmissions that enable WLAN sensing measurements to be performed
- Exchange of WLAN sensing feedback and information
"As radio waves move through a space and interact with people, they create distinctive patterns that can be captured and analyzed. These patterns are comparable to images produced by cameras, but they are formed using radio signals rather than light. "
The concept sounds not unlike like the multispectral imaging produced by Geordi's visor in TNG.
Seems conceptually possible, but likely too much computing power and observing time (to build up and learn each individual's pattern in that part of the RF band), at least in current times.
I'm sure it could be developed to work in the field, but what is the use case where it pays off to make the silly-money investment to make it happen? Especially so when it's far easier to simply notice pings and get better data when approximately everyone always carries their mobile phone.
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’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?
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.
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:
https://www.xfinity.com/hub/smart-home/wifi-motion
Yeah, it can and will be refined, but the major limiting factor is resolution. Wi-Fi radio waves are just too big to get a very clear image.
6 cm is too big? It’s big enough to get an idea of people moving around. And what about the 5 cm wave of 6G Wi-Fi?
But then we can talk about all the millimeterwave signals that are bouncing around everywhere.
like i mentioned in another comment, do you really need good resolution for gait analysis? You also have people carrying their phones inside the house all the time, so you know what bssid is associated with that coarse movement. and if you have access to their ap/router combo, you can tell what IP that device has and what domains it's been visiting.
Let's say you visit a friend in a different city, the same ISP controlling their router, can use your mac, but even if you turn off your wifi or leave your phone in your car, your volume profile and gait can betray you. how you sit, how you lean, how you turn. I'd wager, if 6-10 distinct "points" can be made out and associated with a person, that's all that's needed to uniquely identify that person after enough analysis of their motion, regardless of where they go in the world.
Imagine if they're not using one AP, but using your neighbors AP as well, two neighbor APs and your own can triangulate and refine much better.
for now ...
No this is fixed by physics. 5ghz waves are about 60mm wavelength.
Your resolution limit is about 30mm as a result.
Add a nice prior from a photograph, combine multiple measurements and presto you can pick out a person from a crowd with reasonable accuracy. No?
Wifi 7 includes 6Ghz band but fair enough
There are techniques that can reduce that limit when you have multiple signals, though whether they can be combined with this technique isn’t clear.
This has already been an area of research, both publicly, and most likely in private/government defense research. In a targeted situation, i.e. surveillance of a household of 6, this would work easily enough...but I doubt there is enough information to provide reliable (high AUC) tagging of ID in a public scenario oh hundreds to thousands of individuals.
https://www.theregister.com/2025/07/22/whofi_wifi_identifier...
> Researchers in Italy have developed a way to create a biometric identifier for people based on the way the human body interferes with Wi-Fi signal propagation.. can re-identify a person in other locations most of the time when a Wi-Fi signal can be measured. Observers could therefore track a person as they pass through signals sent by different Wi-Fi networks – even if they’re not carrying a phone.. their technique makes accurate matches on the public NTU-Fi dataset up to 95.5 percent.
I bet there is.
Off the top of my head, I bet body composition combined with gait analysis would be enough to uniquely identify an individual.
if it's a public scenario, you don't need that, they're using wifi on people's persons to id them. The concern is more gait analysis, and by some accounts even lip reading is possible with mm-wave 5g.
> Even Xfinity has motion detection in homes using this technique now
WiFi presence detection is a completely different problem. If the WiFi environment is changing past a threshold, return a boolean yes or no. It can't actually tell if someone is present or if the environment is just changing, such as a car driving close enough to reflect signals back in a certain way.
Doing mass surveillance where you detect individual people in a random home environment isn't the same thing at all. All of these "could" claims are trying to drawn connections between very different problems.
You'll have to explain that a bit more. Isn't the threshold detection analyzing radio signal data? For identifying people, you don't need to reconstruct their face or fingerpring using that data. you just need to fingerprint them.
With gait analysis for example, it's only looking at a handful of data points, the way we walk is very unique. lip-reading, i can see how that's a stretch, but out movement patterns and gait are disturbances in radio waves. If you're using just one person's wifi, that sounds difficult, but if you're collecting signal from multiple adjacent wifi access points, it's more realistic to build a very coarse motion representation, perhaps with a resolution no finer than 1 cubic ft, but even with more coarse representations, gait can be observed.
Even gait aside, the volume profile of a person and their location in the house alone are important data points, couple that with the unique wifi identifier or IP, you can make a really good guess at who the person is, and what room they're in.
Insufficient granularity of data
Only if wifi is radically increased in frequency, power, directionality or antenna size. And i mean way beyond practicallity. It would be easier to identify people by the sounds of thier footsteps, something easily done through anything with a microphone. With three microphones, you can track that movement to the inch.
or if wifi from mobile devices, and your neighbor's APs and their wifi devices is collated to build a fine-enough picture of movements.
the article is off-base with wifi. the real story is in 6G cellular.
there is a working group at 3gpp, an EU-funded research group (6th sense, Open6GHub), universities (NCSU, Bristol), and many companies working very hard right now on proposals to include "integrated/joint sensing and communication" (ISAC/JCAS) in the 6G spec.
ISAC means adding mmWave to 6G (ostensibly for speed, but also) to build a high-fidelity 3d realtime "digital twin" of the real world that can see through walls, owned and operated by your telecom provider.
> A very exciting innovation that 6G will bring to the table would be its ability to sense the environment. The ubiquitous network becomes a source of situational awareness, collating signals that are bouncing off objects and determining type and shape, relative location, velocity and perhaps even material properties. With adequate 6G solutions for privacy and trust, such a mode of sensing can help create a “mirror” or digital twin of the physical world in combination with other sensing modalities.
https://www.nokia.com/about-us/newsroom/articles/nokias-visi... https://www.bell-labs.com/institute/blog/building-network-si...
there's been a testbed deployment in a German hospital for "non-invasive" monitoring of vitals; which sounds to me like it can literally see a heartbeat.
https://www.nokia.com/about-us/news/releases/2024/12/17/noki...
truth is, this is the nature of wireless radios. we can't keep improving bandwidth and latency without also turning the radio into a camera. i'm disturbed by the inevitability.
> ISAC means adding mmWave to 6G (ostensibly for speed, but also) to build a high-fidelity 3d realtime "digital twin" of the real world that can see through walls, owned and operated by your telecom provider.
"See through walls"
There used to be a great video on youtube of a very high power 60GHz signal being blocked by a door. Sad I can never find it. E Band isn't much better.
IIRC the 60GHz radio is being left out of a lot of 5G deployments because the slight benefits don't outweigh the cost.
This is a pretty common thing for mmWave (or near mmWave) to be deployed with massive fanfare and then be slowly phased out of existence. I am decidedly not writing this on a WiGig docking station.
I dont see telcos wanting to constantly broadcast extra mmWave for little to no added benefit, especially not in all directions. Likewise, regulators are going to choke on that. And the class/band license schemes would have to be updated, to remove interference from devices already using those bands as they are about to have a constant background level of interference. E-Band PTP users, of which there are many, wont give up their high capacity links to weird 6G omni broadcasts without a fight.
I tell you what however, having a button you can press that would map the environment for alignment sounds like a maybe use case here. Better than a camera for detecting new obstructions when links go down.
They might also add more bands to the whole automatic MIMO backhaul trick they have been pursuing.
Great. Now you’re telling me the chicken wire embedded in my walls isn’t sufficient, and I’m going to have to go with grounded sheet metal?
Bruce Wayne implemented this almost 2 decades ago in The Dark Knight. EU innovation moving at a snail's pace as usual /s
Yes but this is just the start and its already good enough for an ICE car to park outside your house and check if you're home and what room you're in.
They can do that by looking at the cars in my driveway/garage and or just watching the windows for any period of time. Plus my phone. If <insert 3 letter agency> agents are sitting outside of your house, they aren't going to drive away because you pull the plug on the router and suddenly deprive them of BFI packets.
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.
There'll be an update where a first responder can send a special packet to an SSID that will enable these high rate packets without needing to join the wifi. It'll be secure where only the good guys will know about it so that it won't be able to be used nefariously. /s
Unless they start storing data about your specific gait & posture, skull shape, limb dimensions and build up a "fingerprint" of your body.
You mean like those scanners at the airport?
Please submit full body 3D scan for verification, otherwise discord will lock you to the "kids only" section and mock you mercilessly.
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.
WiFi AP's already do a lot of tracking and measurement just to improve signal fidelity and effective throughput. Why wouldn't those same techniques be useful for more general object tracking? Of course using a single AP to attempt to track movement in real-time is unlikely to have great results, but with several APs and enough compute triangulation should improve results.
> Why wouldn't those same techniques be useful for more general object tracking?
These demos use machine learning to train against a known environment.
Basically, pattern matching changes in the signals against a very controlled set of training data.
You can use WiFi signals to detect that something is changing in the environment, but without the machine learning with controlled input data you don't know what it actually means. This is how WiFi presence detection works, but it won't tell you if it's a person moving through the house or your cat walked in front of the router.
today's tech demos are tomorrow's everyday
Exactly. People are wrong to dismiss this as they're doing in this thread.
LLMs were useless back in 2021.
If I was interested in mass surveillance I would combine the radio data (WLAN, BT, ...) with the camera feed. If you then see the same person with ML, you can correlate that with radio's. You can even do that with cell towers with anonymous SIM, especially if combined with public transport camera feed or ALPR/ANPR.
HEADLINE: Electromagnetic radiation can be used to see!!!!
Right, that's what your eyes do. Radio is much longer wavelength than visible light (~5-10cm). So at best it offers extremely crappy resolution unless - you're doing something clever with second order information.
Yes it's in a controlled environment not in a real world noisy environment. But this is more stealthy than a camera and could potentially work with non-line-of-sight or even through walls.
And based on that I could imagine with a combination of a camera and this method, you could train the model on data where both the camera and this method is seeing the individual and then continue to track them with the wifi sensing + the trained model even where the camera cannot see them anymore.
But yea real world is noisy, so it could be very challenging.
When it comes to capability, the phrase “it’s the worst it’s ever going to be” comes to mind.
Yeah I've seen this same type of study done over the years with the same dire warning. But like you pointed out it's just extremely labor intensive when it's simply easier to attack phones, security cameras or any other smart device that can be easily hacked. Or just install your own bugs.
Would not be surprised to see this get more traction right now due to the political climate.
Yeah this is one of those "cool demo" research results that is completely impractical in the real world that is sold (probably by university PR departments) as an actual viable technique that might have real-world implications.
We've seen it before with things like taking photos around corners.
And no, it isn't like the Wright flyer and a bit crap now but in 40 years we have jet planes. This will never get significantly better.
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?
Android has been doing this for a while, too
windows 11 also has it.
This is going into the next Wifi standard specifically to get this data off of normal wifi traffic.
In a dynamically changing environment (from the perspective of Wi-Fi signal), this will be difficult but not impossible with modern applications of ML algorithms. We worked on this technique back in 2016-18 at the University of Toronto WIRLab; take a look at the results video from back then. I think the person is somewhat identifiable. https://www.youtube.com/watch?v=lTOUBUhC0Cg
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...
>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...
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=%...
Edit: That article isn't about the Nest Protect (smoke detector), it's about the Nest Secure, an alarm system.
How many people have Alexa devices vs wifi? I got gifted an Amazon Echo Dot some years ago. We set it up and switched it off later the same day because it felt creepy to have the thing listening to everything we said.
That reminds me of the other story where the Pixel phones come with a microphone that turns on every time you make a call!
The phone actually records audio and sends it remotely to someone else.
Wait a minute...
Every capacitor can be a potential microphone ...
Make that "every vibrating surface can be a potential microphone ..."
The laser on a hotel window experiment comes to mind.
Or an adapted Theremin
https://en.wikipedia.org/wiki/The_Thing_(listening_device)
with a high speed camera any vibrating reflective object like a potato chips bag can become a weak microphone if you have line of sight even behind a soundproof window: https://www.youtube.com/watch?v=FKXOucXB4a8
> 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...
You are confusing it with the earlier methods. This is similar but not the same method that doesn't use RSSI or CSI and it is passive.
This approach relies solely on the "unencrypted parts of legitimate traffic". The attacker does not need to send any packets or "generate" their own traffic; they simply "listen" to the natural communication between an access point and its clients.
BFI is much more complex than simple signal strength. RSSI is an aggregation of information that the researchers describe as "not robust" for fine-grained tasks In contrast, BFI is a high-resolution, compressed representation of signal characteristics. This rich data allows the system to distinguish between 197 different individuals with 99.5% accuracy, something impossible with basic RSSI.
While older CSI methods often focused on walking directly between a specific transmitter and receiver (Line-of-Sight), BFI allows a single malicious node to capture "every perspective" between the router and all its legitimate clients.
Also CSI requires specialized hardware and custom firmware, this one isn't, just wifi module in monitor mode.
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?
Given the number of publications about curing <pick your uncured disease> over several decades using varying techniques, can you recommend a good review article disproving all of them?
Answer: no need, if it had been cured, it would be cured. And it is not.
My point being that many publications saying "towards X" may mean that we are making some progress towards X, but they don't mean at all that X is possible.
I don’t think anyone has ever tried to publish something disproving all of the gait analysis claims. That would be an odd sort of thing. But I have not seen anything come to something that we could call productized and reliable. It’s relatively easy to publish theoretical papers. Much harder to show it working reliably in the wild.
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.
> 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?]
It's at least possible to record heart rate with wifi, so that suggests a broad variety of biometrics can be recorded.
https://arxiv.org/abs/2510.24744
Could? It has, long time ago:
The first iPad did not have GPS module. It has location system, though. It worked by listening to WiFi and knowing the location of the routers. The list of them updated over the air.
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.
First this is not just Android. Apple does the same thing. You can buy an iPad which physically does not have any GPS hardware and it can reasonably tell you where you are. Personally I first learned of this feature when I bought a second-generation iPad, so it’s been there a while ago.
Second, it is a logical leap to assume Google knows everything already. They could for example build this nearby Wi-Fi based location querying API with privacy in mind, by purposefully making it anonymous without associating it with your account, going through relays (such as Oblivious HTTP), use various private set intersection techniques instead. It is tired and lazy to argue that just because some Big Tech has the capability of doing something bad therefore they must already be doing it.
> Second, it is a logical leap to assume Google knows everything already. They could for example build this nearby Wi-Fi based location querying API with privacy in mind
In which world are you living?
> It is tired and lazy to argue that just because some Big Tech has the capability of doing something bad therefore they must already be doing it.
It has the capability of doing something bad, and it has a history of doing it. Better not forget the last part.
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.
This is a defeatist attitude.
Run grapheneos!
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.
This "could become" sounds exactly like when you look at a cool robotics project, and when you ask the researcher what it could be used for, they say "it could be used for search & rescue after a natural disaster".
The truth is that it's cool research that currently has zero use-case. But a) journalists would not write about that and b) researchers may try to use examples to explain what their research does. Probably researchers are tempted to find a cool use-case of course, because it's better for them if journalists write about their research.
This sounds like cool research that is not remotely close to becoming an invisible mass surveillance system.
Thanks to this disaster of a website that prompts my browser to accept notifications, and autoplays a video ad that hijacked my audio output and shifted the content I was listening to over to the internal computer speaker.
Paper: https://dl.acm.org/doi/epdf/10.1145/3719027.3765062
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.
Funny how mass surveillance concerns are popping up here and there these days. That boat sailed 20 years ago.
WiFi Could Become an Invisible Mass Surveillance System
Highly unlikely and would be a waste of effort and resources. In the real world we are already well surveilled by cameras, microphones, satellites, cell phones, televisions, modern vehicles with a large number of cameras, web enabled doorbell cameras, refrigerators, AirTags, robot vacuum cleaners that map our home and monitor us, anything bluetooth enabled and that is even before actual spy devices like laser microphones that can turn most windows into a giant microphone.
All of these methods are far more attainable without trying to recreate microwave imaging that has been used by the feds for ages and the feds use a handheld device vs. this complex lab setup and this is even before we talk about advanced high resolution milspec FLIR which some companies have managed to get into serious trouble for selling to sanctioned countries for ITAR violations.
This reminds me of those side channel attacks in crypto. Maybe it works, but any adversary most certainly has easier ways of surveilling you, like hidden cameras with facial recognition.
I was really impressed that a ESP32 Antenna Array Can essentially make a WiFi camera - it uses both time and phase differences to localize based on MAC addresses (which are sent plaintext) https://www.youtube.com/watch?v=sXwDrcd1t-E
Yes, that’s a noteworthy project that has some good use cases!
That makes sense. Wi-Fi uses radio waves, part of the light spectrum. Like our eyes or cameras can watch and record, Wi-Fi can also be used for this purpose.
There are much better invisible mass surveillance devices like the one you carry around in your pocket every day.
Elevator pitch: ankle monitor phone case
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).
1: https://www.tommysense.com/
Correct me if I'm wrong but assuming they didn't already know your identity, wearing a mask for instance would prevent profiling you based on your radio wave constructed facial features.
WiFi is already part of invisible mass surveillance systems, though not in the way described in the article. It's part of how cell phones fix location, based on nearby wifi endpoints, which is then sent to google, apple, every app, every advertiser, etc.
And you could surveil them as well, and then shoot them a directed EMP to fry their circuits.
WiFi Sensing is part of Wi-Fi 7 and present in most recent laptops and smartphones. Local NPU machine learning can be combined with WiFI radar. Malware can attack phone and radio basebands and exploit this capability. It can uniquely fingerprint human biometrics, measure breathing rate, record keystrokes and more. Thousands of academic papers have been published in the last 15 years on "device free wireless sensing", before the capability was ratified by IEEE as 802.11bf. It's being rolled out commercially. Mitigations include drywall or insulation with a layer of RF shielding.
"Xfinity using WiFi signals in your house to detect motion", 500 comments, https://news.ycombinator.com/item?id=44426726#44427986
"Wi-fi signal tracks heartbeat without wearables", 80 comments, https://news.ycombinator.com/item?id=45488908
2022 laptop demo of respiration sensing, https://www.intel.com/content/www/us/en/research/respiration... | https://community.intel.com/t5/Blogs/Tech-Innovation/Client/...
2025 biometric signature, https://www.theregister.com/2025/07/22/whofi_wifi_identifier...
> Researchers.. developed.. a biometric identifier for people based on the way the human body interferes with Wi-Fi signal propagation.. CSI in the context of Wi-Fi devices refers to information about the amplitude and phase of electromagnetic transmissions.. interact with the human body in a way that results in person-specific distortions.. processed by a deep neural network, the result is a unique data signature.. [for] signal-based Re-ID systems
Caveat: Indoors. However, since indoors is typically a private space, the degree of surveillance depends on the owner of the space. Civilians can only compel government agencies to make sure that government buildings do not enable tracking. We won't be able to stop Walmart, they can always play the security card which trumps privacy every time.
Walmart has no need for this, they can already surveil you better with actual cameras and microphones.
You're carrying a mass surveillance system in your pants pocket
hah. Could.
At university over a decade ago, we were looking at using Bluetooth/WiFi signals to create live room maps for military applications.
Since then, the tech has only got better.
I'm skeptical; this seems like a pretty crappy way to do surveillance. Cameras give you much more information.
I remember reading about this in a Cory Doctorow novel decades ago, Eastern Standard Tribe, I think.
Cool spooky concept, but seems like this could be easily foiled by shoving some aluminum foil into one's pockets or wearing thermal clothing in the winter. Or moving furniture around.
My cheapo Amazon desk is steel framed, and the monitors have all sorts of metal and signals running through them. I know it impacts wifi because my wifi-connected printer gets crappy signal on one side and decent signal on the other. Good luck getting a positive ID via wifi when I'm sitting at it.
Likewise I don't see how this survives in the real world for a mass surveillance application. Any "signature" will be in constant flux as environments change, in terms of everything from crowds to weather. I'll need to see a demo outside of a controlled environment before I start trying to obfuscate my signature or remodel my house to run Ethernet everywhere.
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.
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.
If the metal bits are floppy enough it should add quite a bit of noise
Cameras just use light waves and are already a mass surveillance system.
Reminds me of the xfinity in-home wifi motion detection, discussed here: https://news.ycombinator.com/item?id=44426726
> 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
How good is ethernet over electrical sockets these days. I had one about 15 years ago maybe, but it wasn't that good.
Has tech changed. I'd use it over my wifi setup if its was fast.
This tech is known as BPL(broadband over powerline) if you want to look further into it.
I used the regular home power stuff many years ago and the speeds were pretty bad and the network loss was unreliable.
My understanding is that it has improved in some circumstances, but if the connection ends up "hopping" through your breaker you get back to garbage speeds.
In theory you can get 2 Gbps speeds, but in practice it seems like still around 500 Mbps. I don't know if the loss has improved but it was a significant problem before, since even a low loss will render a connection unusable.
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.
So, should I start walking around with a jammer or something?
Wait a minute while I don my tin-foil pants.
What about rotating MAC address?
This has nothing to do with MAC addresses.
Not directly, but presumably any device you have on you would be important for associating a profile with an individual.
Scary title, 3 month late into the party… really we don’t deserve better articles with non-dramatic content, much faster?
Xfinity does it or at least say they do.
802.11bf WLAN Sensing Task Group
https://www.ieee802.org/11/Reports/tgbf_update.htm
Task Group bf is expected to develop an amendment that defines modifications to the IEEE 802.11 medium access control layer (MAC) and to the Directional Multi Gigabit (DMG) and enhanced DMG (EDMG) PHYs to enhance Wireless Local Area Network (WLAN) sensing (SENS) operation in license-exempt frequency bands between 1 GHz and 7.125 GHz and above 45 GHz.
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- Stations to inform other stations of their WLAN sensing capabilities
- Request and setup transmissions that enable WLAN sensing measurements to be performed
- Exchange of WLAN sensing feedback and information
Perhaps we should ask be using aluminium foil hat now
Could? Is mate. Is.
Who cares, we have nothing to hide.
LOL @ "Could"
Nothing says "out of touch with reality" like 'murcan media.
"As radio waves move through a space and interact with people, they create distinctive patterns that can be captured and analyzed. These patterns are comparable to images produced by cameras, but they are formed using radio signals rather than light. "
The concept sounds not unlike like the multispectral imaging produced by Geordi's visor in TNG.
Seems conceptually possible, but likely too much computing power and observing time (to build up and learn each individual's pattern in that part of the RF band), at least in current times.
I'm sure it could be developed to work in the field, but what is the use case where it pays off to make the silly-money investment to make it happen? Especially so when it's far easier to simply notice pings and get better data when approximately everyone always carries their mobile phone.
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’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.
Because a device to receive WiFi signals could be hidden behind a wall outlet with no sign that it is installed?
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.
To detect and track people? As someone who manages a modern wifi system, I have doubts. This isn’t a could, this is a never.
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.
“Could become”
Already is and widely used for exactly what the article worries about
Not even close. Now I feel like I need to make an X account that just posts headlines after s/could/will never/.
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?
Not surprised, related: https://news.ycombinator.com/item?id=46920315
That's more than related
Why is this downvoted. Is supposed to read: “Not surprised. Related:”