PPGSecure: Biometric Presentation Attack Detection Using Photopletysmograms

Abstract

Authentication of users by exploiting face as a biometric is gaining widespread traction due to recent advances in face detection and recognition algorithms. While face recognition has made rapid advances in its performance, such facebased authentication systems remain vulnerable to biometric presentation attacks. Biometric presentation attacks are varied and the most common attacks include the presentation of a video or photograph on a display device, the presentation of a printed photograph or the presentation of a face mask resembling the user to be authenticated. In this paper, we present PPGSecure, a novel methodology that relies on camera-based physiology measurements to detect and thwart such biometric presentation attacks. PPGSecure uses a photoplethysmogram (PPG), which is an estimate of vital signs from the small color changes in the video observed due to minor pulsatile variations in the volume of blood flowing to the face. We demonstrate that the temporal frequency spectra of the estimated PPG signal for real live individuals are distinctly different than those of presentation attacks and exploit these differences to detect presentation attacks. We demonstrate that PPGSecure achieves significantly better performance than existing state of the art presentation attack detection methods.