Two-factor biometric authentication system based on facial recognition using the SVC model: The case of SENEGAL

The development of digital technologies has profoundly transformed authentication methods, particularly in the context of online examinations and other related areas such as electronic transactions. Electronic signatures, while effective, face security challenges such as identity theft and fraud. This paper proposes an innovative solution by integrating facial recognition with the electronic signature, thus combining a secret code and biometrics to guarantee the authenticity of the signatory. We propose a secure solution using advanced technologies such as Deep Learning with the SVC (Support Vector Classifier) model for facial recognition. Tests on a real dataset have shown that the classification approach outperforms traditional direct comparison methods. This article highlights the importance of integrating biometrics into electronic signature systems to enhance security. It also highlights the need to adapt these technologies to the Senegalese context, where the digital transition and citizens' confidence in digital tools are crucial to encouraging their adoption.