Intelligent Authentication Techniques for Secure Mobile Devices

Abstract

Mobile devices have become an essential part of everyday life, allowing users to access banking, healthcare, social media, and other sensitive services. As the amount of personal information stored on smartphones continues to grow, protecting these devices from unauthorized access has become increasingly important. This project presents a secure authentication system that uses fingerprintbased biometric verification instead of traditional password authentication. The proposed system is developed using Python and Django and applies Harris Corner Detection along with ORB feature extraction to compare fingerprint images during user registration and login. The system verifies whether the uploaded fingerprint matches the one stored in the database before granting access. This approach enhances security by reducing the risks associated with stolen or weak passwords while providing a reliable and user-friendly authentication process. The proposed solution demonstrates that biometric authentication offers improved protection for mobile applications and can be extended to Androidbased systems for secure user access.