Facial Authentication System Utilising Deep Learning with Enhanced Anti-Spoofing and Encryption

In this study, we propose a Facial Authentication System that uses deep leaning in order to be secure, efficient and user-friendly authentication process. Traditional ways of authentication like passwords and PINs are all prone to security threats such as hacking, phishing etc. In addition to this, we embrace biometrics in authentication by adding a feature of face recognition to overcome these challenges. The system's model should be trained using deep learning processing methods so as to rightly detect and authenticate users while putting in place measures against fraudulent access, that are using photos or videos. Further, the system contains OTP verified layers security and also uses password hashing and embedding encryption to protect sensitive biometric information. This has been developed in Flask, OpenCV and deep learning libraries with web-based easy authentication in mind. With high accuracy, real-time detection, and secure encryption techniques, this facial authentication system shows immense possibilities toward applications in banking, enterprise security, and many more industries, which require trustworthy identity verification.