An end-to-end screen shooting resilient blind watermarking scheme for medical images

稳健性(进化) 计算机科学 数字水印 水印 人工智能 加密 计算机视觉 计算机安全 图像(数学) 生物化学 化学 基因
作者
Zongwei Tang,Xiuli Chai,Yang Lu,Sheng Wang,Yong Tan
出处
期刊:Journal of information security and applications [Elsevier BV]
卷期号:76: 103547-103547 被引量:10
标识
DOI:10.1016/j.jisa.2023.103547
摘要

The rapid progress in artificial intelligence and network communication has led to the development of advanced regional medical systems, revolutionizing the way hospitals and patients connect. However, the security of these systems is threatened by the potential breach of medical data, especially sensitive medical images. Existing watermarking schemes have focused on optimizing either imperceptibility or robustness, creating a fundamental trade-off between these two aspects that poses a significant challenge in the field. To address this challenge and ensure the confidentiality and integrity of medical data, this paper proposes an end-to-end screen shooting resistant blind watermarking scheme for medical images. The proposed method offers a robust and reliable solution for the secure transmission and storage of medical images, particularly in the face of screen shooting attacks. To enhance both security and imperceptibility, the scheme employs a novel encryption technique based on BCH codes, resulting in a trinary sequence for watermark images. These watermarks are then embedded in the spatial domain, effectively protecting against unauthorized access while preserving the integrity of the original image. To further enhance robustness, the method introduces a neural network structure specifically designed to resilient screen shooting attacks. By simulating the screen shooting process and incorporating various distortions, this network combines the strengths of residual networks and generative adversarial networks. Moreover, the proposed method introduces a novel loss function that exploits the unique characteristics of the image transformation domain, optimizing both imperceptibility and robustness. In the subsequent experiment, the watermarked images achieved satisfactory results with the highest PSNR and SSIM values reaching 62.563 dB and 0.9999, respectively. The proposed scheme provides an effective solution to protect the privacy and copyright of medical images, effectively addressing a critical security concern prevalent in regional healthcare systems.
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