Real-time Authentication for Electronic Service Applicants using a Method Based on Two-Stream 3D Deep Learning

Document Type : Original Article

Authors

Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran

Abstract

Authentication in cyberspace aims to maintain security, and if it is done with high accuracy, it can be considered 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, the 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 is 99.99%, and the average precision of authentication and identifying people in both CASME and CASME2 databases is more than 99.5%.

Keywords

References

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History

  • Receive Date: 02 August 2022
  • Revise Date: 05 February 2023
  • Accept Date: 28 February 2023

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