Biblio

Facial biometrics have the advantages of high reliability, strong distinguishability and easily acquired for authentication. Therefore, it is becoming wildly used in identity authentication filed. However, there are stability, security and privacy issues in generating face key, which brings great challenges to face biometric authentication. In this paper, we propose a biometric key generation scheme based on face image. On the one hand, a deep neural network model for feature extraction is used to improve the stability of identity authentication. On the other hand, a key generation mechanism is designed to generate random biometric key while hiding original facial biometrics to enhance security and privacy of user authentication. The results show the FAR reach to 0.53% and the FRR reach to 0.57% in LFW face database, which achieves the better performance of biometric identification, and the proposed method is able to realize randomness of the generated biometric keys by NIST statistical test suite.