ONLINE BANKING SECURITY WITH REAL TIME FACE RECOGNITION APPROACH

Online banking has become an essential part of modern banking. Many attacks are successful in accessing social network accounts since the current password-based authentication paradigms are not efficient and robust enough as well as vulnerable to automated attacks. The simplest alternative is complementing the single factor (password-based) authentication process with additional identification elements, such as one-time PIN codes, generated by the user's own device (e.g., the smartphone) or received via SMS. To improve the security of online banking transactions, real-time face recognition technology can be used as a biometric authentication technique. This technology provides a reliable and convenient way of verifying the identity of customers in real-time. The aim of this project is to develop an online banking system that uses real-time face recognition technology for customer authentication. The system will be designed to provide a secure and user-friendly interface that allows customers to carry out banking transactions such as funds transfer, bill payments, and balance inquiries. The system will incorporate a Grassmann Learning algorithm that is capable of capturing and analyzing a customer's facial features in real-time. The algorithm will compare the facial features of the customer with those in the bank's database to verify the customer's identity. Second level verification based on OTP verification in reverse order. The system will provide a secure and user-friendly interface for customers to carry out banking transactions in real-time. In this proposed net banking application notifications are sending to the user regarding banking interface access and amount transaction.