Alsuhibany Suliman A
Department of Computer Science, College of Computer, Qassim University, Buridah 51452, Saudi Arabia.
Sensors (Basel). 2025 Jun 20;25(13):3855. doi: 10.3390/s25133855.
Barcode technology is widely used as an automated identification system that enables rapid and efficient data capture, particularly in retail environments. Despite its practicality, barcode-based systems are increasingly vulnerable to security threats-most notably, barcode substitution fraud. To address these challenges, this paper presents an innovative system for the secure generation and verification of Quick Response (QR) codes using a digital watermarking technique. The proposed method embeds tamper-resistant information within QR codes, enhancing their integrity and making unauthorized modification more difficult. Additionally, a neural network-based authentication model was developed to verify the legitimacy of scanned QR codes. The system was evaluated through experimental testing on a dataset of 5000 QR samples. The results demonstrated high accuracy in distinguishing between genuine and fraudulent QR codes, confirming the system's effectiveness in supporting fraud prevention in real-world applications.
条形码技术作为一种自动化识别系统被广泛应用，它能够实现快速高效的数据采集，尤其是在零售环境中。尽管条形码技术具有实用性，但基于条形码的系统越来越容易受到安全威胁，最显著的是条形码替换欺诈。为应对这些挑战，本文提出了一种创新系统，该系统使用数字水印技术对快速响应（QR）码进行安全生成和验证。所提出的方法在QR码中嵌入防篡改信息，增强其完整性并使未经授权的修改更加困难。此外，还开发了一种基于神经网络的认证模型来验证扫描的QR码的合法性。该系统通过对5000个QR样本数据集进行实验测试来评估。结果表明，在区分真实QR码和欺诈性QR码方面具有很高的准确性，证实了该系统在支持实际应用中预防欺诈方面的有效性。
