Breathing-based Continuous Non-intrusive User Verification Leveraging Commodity WiFi

Huan Dai, Jingjing Jiang, Jiaju Ma, He Huang, and Hongbo Liu

10.23919/JCN.2022.000011

Abstract : This paper opens up a new pathway of the utility of breathing pattern for user verification. We demonstrate that it is possible to capture people’s breathing pattern leveraging commodity WiFi devices. While prior solutions for biometricsbased user recognition usually require dedicated devices (e.g., video cameras or IR sensors), this paper introduces the first general, low-cost breathing-based user verification system using commodity WiFi devices. The proposed system is based on the fact that the breathing pattern always keeps consistent for the same user but distinct among different people. Our innovative method successfully extracts the breathing pattern of different people based on channel state information of WiFi signal to facilitate user verification. The prototype study using two commodity WiFi devices can differentiate people with an average verification accuracy over 90%, suggesting that our breathing-based user verification system using commercial off the-shelf (COTS) WiFi is promising to be one of the most critical methods in biometrics. 

Index terms : Breathing pattern, channel state information, security monitoring, user verification.