QR Code Security Enhancement

The project presents a QR Code-based authentication and data verification system integrated with Machine Learning for secure access control.Traditional authentication mechanisms such as usernames and passwords are prone to attacks including phishing, credential theft, and brute force.To overcome these limitations, the proposed system employs QR codes as digital identity tokens, which are generated and validated through a web-based application built using Django.Users register through the application, and their credentials are securely stored.During login or data access, the system requires the user to upload or scan a QR code.The backend processes the QR image using Python libraries and applies machine learning techniques to ensure the QR content is valid, unaltered, and corresponds to the registered user.This eliminates the dependency on human interaction for verification while enhancing security, reliability, and automation.