在群组通信环境中保护患者隐私，防止医学图像被未经授权地泄露。
Protecting patient privacy against unauthorized release of medical images in a group communication environment.
作者信息
Li Mingyan, Poovendran Radha, Narayanan Sreeram
机构信息
Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA.
出版信息
Comput Med Imaging Graph. 2005 Jul;29(5):367-83. doi: 10.1016/j.compmedimag.2005.02.003.
In this paper, we identify and study an important patient privacy protection problem related to medical images. Following Health Insurance Portability and Accountability Act (HIPAA) mandate on privacy protection of patients' medical records, efforts have been devoted to guaranteeing the confidentiality of data and medical images during storage and transmission via an untrustworthy channel. However, to our knowledge, there has not been any effort towards protecting against unauthorized release of images by an authorized recipient. In this paper, we study the problem of tracing illegally distributed medical images in a group communication environment and identify a set of design requirements that must be met. We propose a fingerprint model suitable for many-to-many multicast, that is computationally efficient and scalable in user storage and key update communication. Simulation results also show that our scheme is highly robust to typical medical image processing and collusion attacks, while yielding high quality watermarked images.
在本文中，我们识别并研究了一个与医学图像相关的重要患者隐私保护问题。遵循《健康保险流通与责任法案》（HIPAA）对患者病历隐私保护的要求，人们致力于确保数据和医学图像在通过不可信渠道存储和传输期间的保密性。然而，据我们所知，尚未有任何措施来防范授权接收者未经授权发布图像的情况。在本文中，我们研究了在群组通信环境中追踪非法分发的医学图像的问题，并确定了一组必须满足的设计要求。我们提出了一种适用于多对多多播的指纹模型，该模型在用户存储和密钥更新通信方面计算效率高且可扩展。仿真结果还表明，我们的方案对典型的医学图像处理和共谋攻击具有高度鲁棒性，同时能生成高质量的水印图像。
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