Source: Karlsruher Institut für Technologie (KIT)
INVISIBLE SURVEILLANCE using ordinary WiFi signals could soon identify and track people with near perfect accuracy, according to researchers in Germany who demonstrated a system capable of recognising individuals without requiring them to carry an active device.
German researchers said standard WiFi routers can identify people by analysing how radio waves reflect off their bodies.
The team used wireless signals and artificial intelligence to create what they described as a new form of surveillance capable of recognising individuals even when their phones are switched off.
“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 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,” the cybersecurity expert explained. “Thus, it does not matter whether you carry a WiFi device on you or not.”
Researchers said turning off a smartphone would not prevent detection because nearby wireless devices connected to the network still generate enough signal activity for the system to function.
The team warned that the technology could transform ordinary routers into hidden monitoring systems operating without attracting attention.
“This technology turns every router into a potential means for surveillance,” said 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 said intelligence agencies or cybercriminals currently have easier methods to monitor people, including hacked security cameras or internet connected doorbells. However, he warned that WiFi networks present a different concern because they are widespread and difficult to detect.
“However, the omnipresent wireless networks might become a nearly comprehensive surveillance infrastructure with one concerning property: they are invisible and raise no suspicion,” Morsbach said.
Researchers said wireless networks in homes, offices, restaurants, airports and public spaces could give the technology broad reach.
The system does not require specialised sensors or expensive hardware. Researchers said earlier approaches relied on channel state information, which measures how radio signals change after reflecting off walls, furniture and people.
The new method instead uses ordinary communication between WiFi routers and connected devices. Devices regularly send beamforming feedback information to routers and researchers said the data is transmitted without encryption, allowing anyone within range to potentially read it.
Researchers also said signal reflections can create multiple views of a person, enabling artificial intelligence systems to learn and recognise individual identities. After training the machine learning model, identifying a person reportedly takes only a few seconds.
Tests involving 197 participants showed the system identified individuals with nearly 100% accuracy, researchers said. They added that recognition remained effective regardless of viewing angle or how participants walked.
“The technology is powerful, but at the same time entails risks to our fundamental rights, especially to privacy,” Strufe said.
Researchers added that they were particularly concerned about the possible use of the technology in authoritarian countries to monitor protesters or track citizens without their knowledge.
They therefore called for stronger privacy protections and safeguards to be included in the upcoming IEEE 802.11bf WiFi standard.
Credit: AI/ScienceDaily.com
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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