HYBRID BIOMETRIC AUTHENTICATION FOR AUTOMATIC TELLER MACHINE

Abstract

Automated Teller Machines (ATMs) are a crucial part of modern life, providing users with the ability to conduct basic banking transactions electronically without the need for bank representatives. These machines are ubiquitous, particularly in developed countries, and their usage is expanding rapidly across the globe. However, this widespread adoption has highlighted significant security concerns for general users. Traditional security measures, such as Personal Identification Numbers (PINs), are increasingly proving insufficient due to issues like card theft, ATM scams, and other security breaches. To address these vulnerabilities, biometrics-based authentication is emerging as a promising alternative. Unlike traditional password or PIN-based methods, biometric authentication uses unique physical characteristics, such as fingerprints, to verify identity. This method offers a higher level of security by making it significantly harder for unauthorized users to access accounts. In this research, we introduce a hybrid biometric authentication system for ATMs, focusing on fingerprint recognition. Our prototype aims to enhance transaction security and provide a more user-friendly experience. By integrating biometric strategies with ATMs for single verification, we aim to reduce the risks associated with PIN-based authentication and improve overall security. This approach not only addresses existing vulnerabilities but also sets the stage for more secure and reliable ATM transactions in the future.