AI Security in Contactless Payments and Education: A Review

Document Type

Article

Source of Publication

Journal of Engineering Education Transformations

Publication Date

9-1-2025

Abstract

In today’s digital economy, contactless credit cards have become central to financial transactions, offering speed and convenience through technologies such as Near Field Communication (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 learning and ransomware targeting card infrastructure—remain underexplored in academic and industrial research. This survey examines the evolving security landscape of contactless credit cards, focusing on AI threats and corresponding defenses. It identifies vulnerabilities in NFC protocols and shows how adversarial 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 technical insights, this work highlights the value of integrating 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, including AI solutions to secure contactless payment ecosystems.

ISSN

2349-2473

Publisher

Rajarambapu Institute of Technology

Volume

39

Issue

Special Issue 1

First Page

20

Last Page

25

Disciplines

Business | Computer Sciences

Keywords

Adversarial ML, Credit Cards, Cybersecurity Education, Edge AI Defenses, Fraud Detection, NFC Security

Scopus ID

105016892224

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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