AI Security in Contactless Payments and Education

In today’s digital economy, contactless credit cards have become central to financial transactions, offering speed and convenience through technologies such as Near Field Commu-nication (NFC), embedded Wi-Fi, and mobile wallets. However, this shift has also expanded the cybersecurity attack surface. While artificial intelligence (AI)-driven fraud detection has advanced, emerging threats—particularly adversarial machine learningandransomwaretargetingcardinfrastructure—remain underexplored in academic and industrial research. This survey examines the evolving security landscape of contactless credit cards,focusingonAIthreatsandcorrespondingdefenses.Itiden-tifiesvulnerabilitiesinNFCprotocolsandshowshowadversarial examples can bypass traditional fraud detection. The study also explores the potential for ransomware and real-time attacks that exploit digital card systems. In parallel, it evaluates AI-based defensive frameworks, outlining their strengths, limitations, and feasibility in resource-constrained environments. Beyond tech-nicalinsights,thisworkhighlightsthevalueofintegrating such real-world challenges into computer engineering education. By linking AI security with embedded systems, protocols, and threat modeling, it proposes a curriculum framework to prepare students for modern cybersecurity demands. Finally, the paper identifies key research gaps and suggests future directions, includingAIsolutionstosecurecontactlesspaymentecosystems.