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Application of Zero-Watermarking for Medical Image in Intelligent Sensor Network Security

Shixin Tu, Yuanyuan Jia, Jinglong Du*, Baoru Han*

Medical Data Science Academy, College of Medical Informatics, Chongqing Medical University, Chongqing, 400016, China

* Corresponding Authors: Jinglong Du. Email: email; Baoru Han. Email: email

(This article belongs to this Special Issue: AI-Driven Engineering Applications)

Computer Modeling in Engineering & Sciences 2023, 136(1), 293-321.


The field of healthcare is considered to be the most promising application of intelligent sensor networks. However, the security and privacy protection of medical images collected by intelligent sensor networks is a hot problem that has attracted more and more attention. Fortunately, digital watermarking provides an effective method to solve this problem. In order to improve the robustness of the medical image watermarking scheme, in this paper, we propose a novel zero-watermarking algorithm with the integer wavelet transform (IWT), Schur decomposition and image block energy. Specifically, we first use IWT to extract low-frequency information and divide them into non-overlapping blocks, then we decompose the sub-blocks by Schur decomposition. After that, the feature matrix is constructed according to the relationship between the image block energy and the whole image energy. At the same time, we encrypt watermarking with the logistic chaotic position scrambling. Finally, the zero-watermarking is obtained by XOR operation with the encrypted watermarking. Three indexes of peak signal-to-noise ratio, normalization coefficient (NC) and the bit error rate (BER) are used to evaluate the robustness of the algorithm. According to the experimental results, most of the NC values are around 0.9 under various attacks, while the BER values are very close to 0. These experimental results show that the proposed algorithm is more robust than the existing zero-watermarking methods, which indicates it is more suitable for medical image privacy and security protection.


Cite This Article

Tu, S., Jia, Y., Du, J., Han, B. (2023). Application of Zero-Watermarking for Medical Image in Intelligent Sensor Network Security. CMES-Computer Modeling in Engineering & Sciences, 136(1), 293–321.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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