Detection of Phishing Link and QR Code of UPI Transaction using Machine Learning

Development of digital payment systems and the evolution of technology give rise to new frauds. With bogus URLs and QR Codes, phishing poses a major danger to transaction security and integrity. The proposed detection of phishing link and QR code of UPI transaction using machine learning delves into the complexity of this important topic, providing information about fraud and enhancing the exploitation of UPI ecosystems. This study intends to overcome this problem by leveraging Machine Learning and AI techniques to prevent fraud and improve security mechanisms. Phishing is a malicious attempt to pose as a reliable source in order to fool people into disclosing private information, including passwords, usernames, or bank account information. Phishing attacks can also be carried out with QR codes, which are a kind of data storage that can be swiftly accessed by a smartphone's camera. User awareness and resistance against phishing attacks. The Universal Payment Interface (UPI) is at the forefront of this disruptive wave due to its ease and efficiency in financial operations. This study investigates not just the historical context of phishing efforts but also the evolving techniques employed by fraudsters to exploit the UPI ecosystem.