全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Enhancing Security in QR Code Technology Using AI: Exploration and Mitigation Strategies

DOI: 10.4236/ijis.2024.142003, PP. 49-57

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

Full-Text   Cite this paper   Add to My Lib

Abstract:

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.

References

[1]  Bashir, H. (2022) Leveraging Technology to Communicate Sustainability-Related Product Information: Evidence from the Field. Journal of Cleaner Production, 362, Article ID: 132508.
https://doi.org/10.1016/j.jclepro.2022.132508
[2]  Huo, L., Zhu, J., Singh, P.K. and Pavlovich, P.A. (2021, January 1) Research on QR Image Code Recognition System Based on Artificial Intelligence Algorithm. Journal of Intelligent Systems, 30.
https://doi.org/10.1515/jisys-2020-0143
https://www.degruyter.com/document/doi/10.1515/jisys-2020-0143/html
[3]  Posey, B. (2022, August 5) Understanding QR Code Security Issues for Enterprise Devices.
https://www.techtarget.com/searchmobilecomputing/tip/Understanding-QR-code-security-issues-for-enterprise-devices
[4]  Malwarebytes (2023, December 15) QR Code: How They Work and How to Stay Safe?
https://www.malwarebytes.com/cybersecurity/basics/what-is-a-qr-code
[5]  Sarker, I.H., Hoque, M.M., Uddin, M.K. and Alsanoosy, T. (2021) Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions. Mobile Networks and Applications, 26, 285-303.
https://doi.org/10.1007/s11036-020-01650-z
[6]  Morikawa, C., Kobayashi, M., Satoh, M., Kuroda, Y., Inomata, T., Matsuo, H., Miura, T. and Hilaga, M. (2021) Image and Video Processing on Mobile Devices: A Survey. The Visual Computer, 37, 2931-2949.
https://doi.org/10.1007/s00371-021-02200-8
[7]  Daengsi, T., Pornpongtechavanich, P. and Wuttidittachotti, P. (2021) Cybersecurity Awareness Enhancement: A Study of the Effects of Age and Gender of Thai Employees Associated with Phishing Attacks. Education and Information Technologies, 27, 4729-4752.
https://doi.org/10.1007/s10639-021-10806-7

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133