Securing QR Code Infrastructure Using AI to Detect MaliciousActivity

Abstract

Quick Response (QR) codes have become an
essential component of modern digital systems,
widely used in applications such as mobile
payments, authentication, ticketing, and information
sharing. However, their rapid adoption has
introduced significant cybersecurity risks, including
phishing attacks, malware distribution, and
malicious redirection. Traditional QR code scanners
merely decode embedded data without verifying its
authenticity, leaving users vulnerable to cyber
threats.
The proposed system achieves an accuracy
exceeding 96% and supports real-time QR scanning
via image upload and webcam. The framework is
scalable, user-friendly, and suitable for deployment
across industries such as banking, healthcare, and
public infrastructure, thereby enhancing trust and
security in QR-based systems.