Phishing Detection in Advanced QR Code Attacks: Challenges and AI-Driven Solutions

QR code-based phishing attacks have emerged as a significant cybersecurity threat, exploiting traditional email security solutions that fail to detect QR-based phishing since they contain neither embedded links nor text-based URLs. This paper explores the challenges of QR phishing attacks, analyses why current security mechanisms are ineffective, and proposes an AI-driven detection framework. A dataset-driven approach is adopted to assess detection accuracy, with experimental evaluations comparing traditional, machine learning, and hybrid AI-based detection techniques.