عنوان مقاله [English]
Authentication in cyberspace aims to maintain national security, and if it is done with high accuracy, it can be considered as a passive defense for the continuity of service delivery under different conditions. The present research aims to propose a fully applicable method for authentication of the applicants for electronic services in real-time. In order to prevent the possible tricks of the users, in the proposed method, identification of facial muscle movements and iris biometric measurement have been used. The iris creates more reliability and cannot be stolen or faked; because it must be available live. A method based on two-stream 3D deep learning is proposed for authentication and simultaneously identifying facial muscle movements and distinguishing a living person from an image. According to the evaluations, it was found that the proposed method provides significant assurance for public use and is applicable in real and practical conditions. Using the proposed method, the accuracy of the proposed method is 99.99%, and the average precision of authentication and identifying people in both CASME and CASME2 databases is more than 99.5%.