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WiFi signals could potentially be used to identify people and map their surroundings without cameras or requiring individuals to carry connected devices, according to cybersecurity researchers.
Researchers say the technique works by analyzing how radio waves propagate through a space. By studying changes in the signals as they interact with people, walls, furniture and other objects, it may be possible to create an image of a person and their surroundings.
“By observing the propagation of radio waves, we can create an image of the surroundings and of persons who are present,” said Professor Thorsten Strufe of KASTEL, KIT’s Institute of Information Security and Dependability.
He explained that the approach works in a way similar to a conventional camera, except that it uses radio waves instead of light waves to recognize people and their environment.
A key feature of the technology is that the person being monitored does not need to carry a smartphone, smartwatch or other WiFi-enabled device.
“Thus, it does not matter whether you carry a WiFi device on you or not,” Strufe said.
Turning off a person’s own devices may also not prevent such monitoring. Researchers say it could be sufficient for other WiFi-enabled devices in the surrounding area to remain active.
The researchers warned that the findings could raise significant privacy concerns because WiFi networks are already widespread in homes, offices, restaurants and public spaces.
“This technology turns every router into a potential means for surveillance,” said Julian Todt of KASTEL.
He said a person who regularly passes a café with a WiFi network could potentially be identified without knowing it and recognized later, including by public authorities or companies.
Felix Morsbach noted that intelligence agencies and cybercriminals already have simpler methods of monitoring people, such as accessing CCTV systems or connected video doorbells.
However, he said the widespread availability of wireless networks could eventually create an almost comprehensive surveillance infrastructure with one major difference: the networks are invisible and do not immediately raise suspicion.
Unlike conventional security cameras, WiFi networks generally provide no visible indication that their radio signals could potentially be analyzed to determine who is nearby.
Earlier methods of detecting people through wireless signals have often relied on specialized hardware or more complex measurements. Some systems use LIDAR sensors, which determine distances by transmitting light and analyzing reflected signals.
Other WiFi-based techniques rely on channel state information (CSI), which measures how wireless signals change as they travel through an environment and interact with walls, furniture, people and other objects.
The researchers’ findings highlight how existing wireless infrastructure could potentially be repurposed for sensing and identification, raising questions about privacy protections as WiFi-based monitoring technology continues to develop.