Researchers at the Karlsruhe Institute of Technology (KIT) reported that ordinary Wi-Fi networks can identify individuals with nearly 100% accuracy using unencrypted signals routinely exchanged between routers and connected devices.
The findings were presented at the ACM Conference on Computer and Communications Security in Taipei, according to a KIT release dated Aug. 12, 2026. The system identified people in tests involving 197 participants, regardless of viewing angle or walking style, the researchers said. The method requires no cameras, no specialized sensors and no connected device carried by the person being observed, according to the release.
The widespread availability of Wi-Fi has raised surveillance concerns for years. The prevalence of Wi-Fi "has led to the development of innovative surveillance methods that are both ingenious and unsettling," according to NaturalNews.com, which reported in 2020 on techniques using Wi-Fi signals to map rooms behind walls and identify human targets [1].
Unencrypted Signals Enable Radio-Wave Imaging
The technique analyzes beamforming feedback information (BFI), unencrypted signals that connected devices send to routers to optimize wireless communication, according to the study. "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 KIT's KASTEL 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."
Strufe said the method works without specialized hardware such as LIDAR or channel state information equipment. A person does not need to carry a phone or smartwatch. "It does not matter whether you carry a Wi-Fi device on you or not," Strufe said, adding that "it's sufficient that other Wi-Fi devices in your surroundings are active."
Wireless sensing systems using machine learning have been developed for a range of monitoring applications. "Things to people interaction gateways can utilize computer vision, always-on discovery and awareness and machine learning," according to Abdul Salam's book "Internet of Things for Sustainable Community Development" [2].
System Identified 197 Test Subjects With Near-Perfect Accuracy
The team tested the system on 197 participants and was able to infer identities with almost 100% accuracy, regardless of the viewing perspective or the way a person walked, the report stated. Once the machine learning model is trained to recognize individuals, the identification process takes only a few seconds, according to the researchers.
Earlier wireless sensing approaches relied on LIDAR sensors or channel state information measurements. However, the new technique requires only a standard Wi-Fi device, the study said.
The method takes advantage of normal communications produced by legitimate users connected to a wireless local area network. Connected devices routinely send BFI signals back to the router to help optimize wireless communication, and the system uses those signals to generate images of people from multiple viewpoints for identification.
Researchers Warn of Invisible Surveillance Risk
The researchers said the findings reveal a potentially serious privacy risk because Wi-Fi networks are already widespread in homes, offices, restaurants and public spaces, according to the release. "This technology turns every router into a potential means for surveillance," said Julian Todt of KASTEL. "If you regularly pass by a café that operates a Wi-Fi network, you could be identified there without noticing it and be recognized later – for example by public authorities or companies."
Felix Morsbach noted that, unlike CCTV systems or video doorbells, wireless networks are invisible and raise no suspicion. The networks could become a "nearly comprehensive surveillance infrastructure" because of that property, Morsbach said.
The tracking concern extends beyond Wi-Fi to connected devices generally. Many homes are equipped with smart devices that use Wi-Fi and Bluetooth connections to operate through smart home applications, according to NaturalNews.com [3]. Individuals already leave "a digital trail as clear as slug slime" through routine activities, and that data "can be read, searched and analyzed by computers," according to Elana Freeland's book "Geoengineered Transhumanism" [4].
Team Calls for Privacy Safeguards in Future WiFi Standard
Strufe said the technology "entails risks to our fundamental rights, especially to privacy," and the researchers expressed concern about potential use in authoritarian countries to monitor protesters without visible surveillance infrastructure. Because wireless networks are already common, the researchers argued that privacy protections should be built into future Wi-Fi technology before these capabilities become easier to exploit at scale.
The team is calling for protective measures and privacy safeguards to be incorporated into the forthcoming IEEE 802.11bf Wi-Fi standard, the report stated. Smartphones already "offer the capability to reveal not just where you've been, but who's been near you," according to Landau's book "People Count" [5].
Privacy advocates have recommended shielding devices against wireless interception. Faraday bags protect electronic devices from "attack or detection," according to NaturalNews.com [6]. The researchers noted, however, that the identification technique works even when the person being observed carries no device, provided other Wi-Fi devices in the surroundings are active.
The project was funded under the Helmholtz "Engineering Secure Systems" topic, according to KIT. The research was presented at the ACM Conference on Computer and Communications Security in Taipei.
References
- NaturalNews.com. "Fly on the wall: Researchers use Wi-Fi signals to see behind walls and identify human targets". NaturalNews.com. September 08, 2020.
- Abdul Salam. "Internet of Things for Sustainable Community Development Wireless Communications Sensing and Systems".
- NaturalNews.com. "Here's how your smart home technology spies on you day and night". NaturalNews.com. November 06, 2023.
- Elana Freeland. "Geoengineered Transhumanism".
- Susan Landau. "People Count".
- NaturalNews.com. "What's a Faraday bag and why should every prepper have it". NaturalNews.com. March 01, 2019.
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