Researchers have demonstrated a way to identify people using ordinary WiFi signals, without requiring cameras or even a phone on the person being monitored.
A team at Germany’s Karlsruhe Institute of Technology (KIT) tested the system on 197 people and achieved almost 100% identification accuracy. It continued to recognize people when they were viewed from different angles or changed the way they walked.
The technique works by studying how WiFi radio waves change as they travel through a room and interact with people and objects.
A normal camera creates an image using visible light. This system effectively does something similar using radio waves, the invisible signals that WiFi routers use to communicate with devices.
The person being identified does not need to carry a smartphone, smartwatch, or any other connected device. Even switching off your own phone would not necessarily prevent tracking, as long as other WiFi devices nearby are communicating.
WiFi devices regularly send information back to a router to help it improve the wireless connection.
This information is called Beamforming Feedback Information (BFI). In simple terms, it tells the router how radio signals are travelling through the surrounding area so it can send them more effectively.
The researchers found that this information can also reveal how people affect those radio waves. Because BFI is transmitted without encryption, someone within WiFi range could potentially collect it without needing special surveillance equipment.
A machine-learning system can then turn these signal changes into patterns resembling images from different viewpoints. Once the system has already learned what a particular person looks like through WiFi signals, identifying them takes only a few seconds.
The researchers say the technology could create serious privacy concerns because WiFi networks are already present in homes, offices, restaurants, and other public places.
In theory, someone repeatedly passing a WiFi-equipped location could potentially be recognized without knowing they were being monitored.
The team warned that such technology could become particularly concerning if used for large-scale surveillance. It is calling for stronger privacy protections to be included in future WiFi standards.
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