Online Transaction Fraud Detection Using Backlogging On E-Commerce Website: A Review

The objective of this research is to investigate the gaps in the existing online transaction fraud detection on e-commerce websites, to propose and develop an online transaction fraud detection using backlogging on e-commerce websites that is safe against fraud and enables simple and efficient transactions and implement security measures to prevent a breach of the proposed system. The system can receive, store, and process data related to the customer who registers and uses the system. Furthermore, the system is expected to provide a better interactive feature in an e-commerce website and be able to detect any fraudulent transactions and can restrict and prohibit transactions carried out by an attacker. The system is expected to be secured with the implementation of authentication, bcrypt hashing algorithm, and One Time Password (OTP). The research is to develop an e-commerce site as a web-based system that can assist in detecting transaction frauds using backlogging on an e-commerce website when a customer purchases products from the seller through the internet using a web browser. This research uses behavior analysis to identify fraudulent online credit card transactions in real-time. The algorithm also uses a multi-layered security-based strategy for the transaction restrictions established by the relevant user. The customer's spending limit is used to classify transactions, which aids in determining if the current transaction is legitimate or fraudulent. Finding out the user's location is vital in detecting credit card fraud. The system is useful in a small-scale website for detecting fraud, and with additional improvements, it might be employed in a large-scale e-commerce website where thousands of transactions can occur simultaneously.