Secure Single-User Authentication System with Facial Identification & Pattern Lock

Abstract

This work describes a comprehensive user authentication system designed for any kind of application, specifically for use in bank authentication systems, incorporating facial recognition, pattern drawing, and spoof detection techniques. Strong security measures are essential to protecting sensitive financial data in light of the growing dependence on digital banking services. The system provides bank customers with a smooth and user-friendly authentication experience by utilizing well-known libraries like Open-CV and face-recognition in conjunction with Tkinter for graphical user interface (GUI) development. It intends to alleviate potential security weaknesses associated with conventional password-based authentication techniques by encoding face features, making pattern construction easier, and providing effective detection of spoofing efforts. In order to give administrators more insight into system usage patterns and improve security, user action logging is also used. The further study aims at enhancing security in financial applications by exploring multi-factor authentication techniques and optimizing spoof detecting algorithms. By offering a safe and easy-to-use solution for guaranteeing consumer data confidentiality and privacy, this system shows the potential to resolve authentication problems throughout the banking industry.