Performance Analysis of QR Phishing Detection Approaches

Abstract

Modern digital interaction is made complete with QR codes, which facilitate quick and easy entry to a variety of services and information. Their adoption in finance, marketing, logistics, and healthcare attests to their versatility as well as the risks they pose in the current digital environment. Among these threats, one of the most significant is QR phishing, wherein malicious users avail themselves of both the natural trust and the apparent ease of usage of QR codes to lure victims into giving up sensitive information, visiting counterfeit websites, or downloading malware. This research will investigate vulnerabilities in QR code systems, explore techniques used in carrying out QR phishing, and analyze actual case scenarios to show the effect of such threats. Besides, it presents sophisticated mitigations with the performance analysis, including cryptographic analysis, blockchain-based authentication, and machine learning-based detection systems with the performance analysis to improve the security of QR code applications to maintain the user trust.