A NOVEL HYBRID MODEL FOR ATM SECURITY USING FACE RECOGNITION AND OTP AUTHENTICATION

An Automated Teller Machine (ATM) is a cash dispensing terminal that allows patrons to conduct financial operations without requiring human assistance, including flows, forfeitures, deposits to be made, and balance inquiries. The security of ATM remains a significant concern, with card skimming, phishing, and unauthorized access being prevalent threats. A wide range of technologies, such as PIN, OTP, biometric, RFID, etc., are used to secure ATM machines. This study presents a survey of various ATM security mechanisms, these technologies have several downsides. The combination of OTP and face recognition technology appears to be superior and more secure than other technologies when compared to other technologies used for ATM security. The integration of these two authentication methods provides a robust defense against various types of attacks, including card cloning, identity theft, and shoulder surfing. The system’s usability and user acceptance are also evaluated, showing a positive response from participants. This research contributes to the development of secure and reliable ATM systems, protecting users’ financial information and preventing fraudulent activities.