Submission + - Researchers identify people through ordinary Wi-Fi with 99 percent-accuracy (tomshardware.com)
Baron_Yam writes: Security researchers at the Karlsruhe Institute of Technology (KIT) in Germany have published a paper demonstrating that unencrypted beamforming data broadcast by Wi-Fi devices during normal operation can be used to identify individuals walking through a room with 99.5% accuracy, regardless of whether the individuals are carrying Wi-Fi devices. The tactic leverages the router's beamforming tech to identify individuals with up to 99.5% accuracy, and it works with existing routers, too.
The system, called BFId, requires no specialized hardware, no access to the target Wi-Fi network, and works even if the person being tracked isn't carrying a wireless device. The team tested the attack on 197 participants, the largest dataset ever used in Wi-Fi-based identification works, and plans to present its findings at the ACM Conference on Computer and Communications Security (CCS) in Taipei.
See GitHub — https://github.com/ruvnet/RuVi... — for your own personal implementation requiring a couple of APs and a couple of ESP32 nodes. You can get full-home per-zone motion and occupancy detection fairly reliably, with the potential for pose detection and in optimal areas even respiration rate. With the right hardware and configuration, you can theoretically get heart rate too.
The system, called BFId, requires no specialized hardware, no access to the target Wi-Fi network, and works even if the person being tracked isn't carrying a wireless device. The team tested the attack on 197 participants, the largest dataset ever used in Wi-Fi-based identification works, and plans to present its findings at the ACM Conference on Computer and Communications Security (CCS) in Taipei.
See GitHub — https://github.com/ruvnet/RuVi... — for your own personal implementation requiring a couple of APs and a couple of ESP32 nodes. You can get full-home per-zone motion and occupancy detection fairly reliably, with the potential for pose detection and in optimal areas even respiration rate. With the right hardware and configuration, you can theoretically get heart rate too.
