Author(s)

Saranya Vaithilingam, Santhosh Aradhya Mohan Shankar

Department of Information Technology, University of the Cumberlands, Williamsburg, KY, USA.

The widespread adoption of QR codes has revolutionized various industries, streamlined transactions and improved inventory management. However, this increased reliance on QR code technology also exposes it to potential security risks that malicious actors can exploit. QR code Phishing, or “Quishing”, is a type of phishing attack that leverages QR codes to deceive individuals into visiting malicious websites or downloading harmful software. These attacks can be particularly effective due to the growing popularity and trust in QR codes. This paper examines the importance of enhancing the security of QR codes through the utilization of artificial intelligence (AI). The abstract investigates the integration of AI methods for identifying and mitigating security threats associated with QR code usage. By assessing the current state of QR code security and evaluating the effectiveness of AI-driven solutions, this research aims to propose comprehensive strategies for strengthening QR code technology’s resilience. The study contributes to discussions on secure data encoding and retrieval, providing valuable insights into the evolving synergy between QR codes and AI for the advancement of secure digital communication.

Artificial Intelligence, Cyber Security, QR Codes, Quishing, AI Framework, Machine Learning, AI-Enhanced Security

Vaithilingam, S. and Shankar, S. (2024) Enhancing Security in QR Code Technology Using AI: Exploration and Mitigation Strategies. International Journal of Intelligence Science, 14, 49-57. doi: 10.4236/ijis.2024.142003.