Designing a Security Framework for Enhancement of Electronic Transactions

With the popularity of e-commerce websites, online transaction options have too gained prominence among customers. Ensuring security is still a major issue that professionals focus on. Though digital transactions enhance customer-merchant experience, there are various risks and challenges involved. Existing techniques such as Address Verification System (AVS), Card Verification Value (CVV), etc. help in verifying customer authenticity. From a customer's perspective, there are no authentication frameworks that will inform them about dishonest merchants. This paper suggests a system model that will use interactive modules to generate a Trust Factor (TF) which will help in detecting fraudulent merchant accounts at financial institutions. This financial technology will generate reports that can be used for analysis to understand the behavior of fraud activities in real time using sophisticated machine learning algorithms, thereby, mitigating merchant and transactional frauds.