Securing ATM Transactions with Facial Recognition-Based Verification System
The current ATM authentication method through PINs exposes users to vulnerabilities such as stolen PINs and cloned cards in traditional systems.This project introduces a Face ATM System that improves safety through deep learning facial identification and mobile authentication instead of the current PIN-based systems.Users receive Face Verification Links through their mobile phones to establish secure account access after CNNs verify their faces.The system delivers security alerts in real-time while keeping banks notified about each transaction to detect problematic behaviour.The system, developed with Python, Flask, OpenCV, and MySQL, presents a security-focused and fraudresistant method that enhances the security profile and user experience of ATM transactions.
Publication Details
- Journal
- IJARCCE
- Published
- 2025-05-05
- DOI
- https://doi.org/10.17148/ijarcce.2025.14490
- Primary Topic
- Biometric Identification and Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00