New Wi-Fi fingerprint system re-identifies people without devices

Italian researchers from La Sapienza University of Rome have developed a novel Wi-Fi fingerprinting system called WhoFi that can re-identify individuals based solely on how their bodies distort Wi-Fi signals, without requiring any carried devices like phones or wearables. By analyzing changes in Wi-Fi signal waveforms—specifically Channel State Information (CSI), which captures amplitude and phase alterations caused by a person’s physical presence—the system creates unique biometric identifiers. Using a transformer-based deep neural network, WhoFi achieved up to 95.5% accuracy in matching individuals across different Wi-Fi-covered spaces, significantly improving on previous methods such as the 75% accurate EyeFi system introduced in 2020. This approach offers a new dimension to surveillance and tracking, as Wi-Fi signals can penetrate walls and operate independently of lighting conditions, unlike cameras. While it may appear more privacy-conscious since it does not capture images, WhoFi raises concerns about passive tracking without consent. The technology builds on advances like the IEEE 802.