Implementation of a Biometric-Based Authentication System on a Website Using Face Recognition Technology

Biometric technology, especially facial recognition, has become a promising solution in improving the security of authentication systems in the ever-evolving digital environment. Traditional authentication methods such as passwords and PINs are vulnerable to cyber attacks, while Face Recognition technology offers individual identification based on unique facial characteristics, which are difficult to forge, and more convenient to use. With the support of machine learning algorithms such as Haar Cascade Classifier and Convolutional Neural Networks (CNN), this system is able to recognize faces in real-time with a high level of accuracy. The implementation of this technology in a web-based authentication system allows for a fast and efficient verification process, and is supported by biometric data encryption and user activity log recording to enhance security. However, challenges such as low lighting and fast facial movements are still aspects that need to be optimized to ensure system reliability.