Utter Innocence: Contactless authentication method based on physiological signals

User authentication is crucial for privacy and security. In daily life, personalized intelligent devices are frequently used. However, these devices are vulnerable to unauthorized access, which can result in serious privacy breaches. To address this problem, this article proposes a user security authentication method that utilizes millimeter-wave radar to perceive human life signals for verification. Firstly, the millimeter-wave radar is used to perceive the user’s breathing and heartbeat signals. Secondly, to eliminate the influence of breath-holding on the verification result, this article adopts the method of recognizing breathing patterns and establishing two channels: one for other breathing signals when not holding breath and another for heartbeat signals when holding breath. Finally, the WPD and MFCC features of the user’s breathing signals, as well as the MFCC features of the heartbeat signals, are extracted. A lightweight neural network, ShuffleNet V2, is used for security authentication. Through a large number of experiments, the verification accuracy is 93.7%.