WiFi Can Identify People With Near-Perfect Accuracy

Karlsruher Institut für Technologie (KIT)

Researchers in Germany are warning that ordinary WiFi networks could become a powerful new form of invisible surveillance. Using standard wireless signals and artificial intelligence, they demonstrated a system capable of identifying people with striking accuracy, even if those individuals are not carrying an active device.

"By observing the propagation of radio waves, we can create an image of the surroundings and of persons who are present," says Professor Thorsten Strufe from KASTEL -- KIT's Institute of Information Security and Dependability. "This works similar to a normal camera, the difference being that in our case, radio waves instead of light waves are used for the recognition," explains the cybersecurity expert. "Thus, it does not matter whether you carry a WiFi device on you or not."

Turning off your smartphone is not enough to avoid detection. According to the researchers, nearby wireless devices connected to the network still generate enough signal activity for the system to work.

WiFi Routers Could Become Hidden Surveillance Tools

The team says the technology could transform everyday routers into quiet monitoring systems that operate without attracting attention.

"This technology turns every router into a potential means for surveillance," warns Julian Todt from KASTEL. "If you regularly pass by a café that operates a WiFi network, you could be identified there without noticing it and be recognized later -- for example by public authorities or companies."

Researcher Felix Morsbach notes that intelligence agencies or cybercriminals currently have easier ways to monitor people, including hacked security cameras or internet connected doorbells. However, he says WiFi networks pose a unique concern because they are nearly everywhere and largely invisible.

"However, the omnipresent wireless networks might become a nearly comprehensive surveillance infrastructure with one concerning property: they are invisible and raise no suspicion."

Wireless networks are now common in homes, offices, restaurants, airports, and public spaces across the world, giving this technology potentially enormous reach.

No Special Hardware Needed

Unlike earlier experimental systems that relied on expensive sensors or specialized equipment, the new method works with ordinary WiFi hardware already found in most homes and businesses.

Previous approaches often depended on channel state information (CSI), which measures how radio signals change after bouncing off walls, furniture, and people. The new technique instead takes advantage of normal communication between WiFi routers and connected devices.

Devices on a wireless network regularly send feedback data known as beamforming feedback information (BFI) to the router. Because this information is transmitted without encryption, anyone within range can potentially read it. Researchers say these signal reflections can effectively create multiple "views" of a person, allowing AI systems to learn and recognize individual identities.

After the machine learning model has been trained, identifying a person reportedly takes only a few seconds.

Near Perfect Accuracy Raises Privacy Concerns

In tests involving 197 participants, the researchers said the system identified individuals with nearly 100% accuracy. The recognition remained effective regardless of viewing angle or how the participants walked.

"The technology is powerful, but at the same time entails risks to our fundamental rights, especially to privacy," emphasizes Strufe.

The researchers are especially concerned about how the technology could be used in authoritarian countries to monitor protesters or track citizens without their knowledge. They are calling for stronger privacy protections and safeguards to be included in the upcoming IEEE 802.11bf WiFi standard.

The project was funded under the Helmholtz "Engineering Secure Systems" topic. The team plans to present its findings at the "ACM Conference on Computer and Communications Security" (CCS) in Taipei.

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