The research introduces a novel authentication system that uses WiFi signals to identify multiple users based on their unique respiration patterns. Unlike traditional authentication methods that rely on passwords, tokens, or wearable devices, MURAL-Fi enables non-intrusive and continuous authentication by analyzing subtle chest movements caused by breathing through standard WiFi infrastructure.
The system leverages multidimensional wireless sensing features, including spatial and motion information extracted from WiFi signals, to separate and track respiration patterns from multiple individuals in the same environment. By combining advanced signal processing techniques with a Siamese neural network, the proposed system can reliably authenticate users even in the presence of interference and involuntary body movements.”