Home / Current Issue / Paper 1716359
Safe Scan – A Proactive Cloud Sandboxed Firewall for QR Code Mitigation
Subject area: Science,Engineering and Technology · Area of research: Cybersecurity
DOI: 10.64388/IREV9I10-1716359
Abstract
QR codes are widely used in digital applications such as online payments, ticketing, and advertisements due to their convenience and ease of use. However, the increasing usage of QR codes has also led to rising security threats, including phishing attacks, malicious links, and fraudulent redirections. Most existing QR code scanners directly decode and open embedded content without performing proper security checks, which exposes users to potential cyber risks. To address this issue, this paper proposes Safe Scan, an Android-based application that enhances QR code security using a proactive approach. The system scans QR codes, extracts embedded data, and analyzes it in a cloud-based sandbox environment before allowing user access. By isolating and evaluating the content, the system identifies suspicious or harmful links and classifies them as safe or unsafe. This approach significantly reduces user exposure to threats and improves overall digital security.
Keywords
Android Application, Cloud Security, QR Code Security, Sandbox Analysis, Threat Detection
References
[1] K. Krombholz et al., “Exploring Phishing Threats through QR Codes in Practice,” NDSS Workshop on Usable Security (USEC), 2024.
[2] S. Gupta et al., “Hooked: A Real-World Study on QR Code Phishing,” arXiv preprint arXiv:2407.16230, 2024.
[3] A. Sharma et al., “Detecting Quishing Attacks with Machine Learning Techniques Through QR Code Analysis,” arXiv preprint arXiv:2505.03451, 2025.
[4] M. Rahman et al., “QRïS: A Preemptive Novel Method for Quishing Detection,” arXiv preprint arXiv:2510.17175, 2025.
[5] S. Jain and B. B. Gupta, “QRphish: An Automated QR Code Phishing Detection Approach,” International Conference on Information Systems Security, 2016.
[6] R. Singh et al., “Exemplifying Emerging Phishing: QR-based Browser-in-TheBrowser Attack,” arXiv preprint arXiv:2505.18944, 2025.
[7] N. Kumar et al., “A Survey on QR Code Phishing Attacks and Detection Techniques,” International Journal of Computer Applications, 2025.
[8] J. Ma et al., “Learning to Detect Malicious URLs,” ACM Transactions on Intelligent Systems and Technology, vol. 2, no. 3, 2011.
[9] Y. Zhang et al., “Phishing Website Detection Based on URL Features Using Deep Learning,” Applied Sciences (MDPI), 2024.
[10] S. Garera et al., “A Framework for Detection of Phishing Attacks Using URL Features,” Proceedings of IEEE, 2007.
How to cite this paper
@article{1716359,
author = {Vinodhini S, Smirthi R},
title = {Safe Scan – A Proactive Cloud Sandboxed Firewall for QR Code Mitigation},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {1885-1888},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1716359.pdf},
abstract = {QR codes are widely used in digital applications such as online payments, ticketing, and advertisements due to their convenience and ease of use. However, the increasing usage of QR codes has also led to rising security threats, including phishing attacks, malicious links, and fraudulent redirections. Most existing QR code scanners directly decode and open embedded content without performing proper security checks, which exposes users to potential cyber risks. To address this issue, this paper proposes Safe Scan, an Android-based application that enhances QR code security using a proactive approach. The system scans QR codes, extracts embedded data, and analyzes it in a cloud-based sandbox environment before allowing user access. By isolating and evaluating the content, the system identifies suspicious or harmful links and classifies them as safe or unsafe. This approach significantly reduces user exposure to threats and improves overall digital security.},
keywords = {Android Application, Cloud Security, QR Code Security, Sandbox Analysis, Threat Detection},
month = {April},
doi = {https://doi.org/10.64388/IREV9I10-1716359}
}