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An efficient scheme for secure domain medical image fusion over cloud

机译：云安全域医学图像融合的高效方案

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摘要

The exponential growth in the medical images is making the healthcare industry move towards cloud-based paradigm, which has vast storage and high end processing facilities. However, moving medical images containing highly sensitive data to third-party cloud servers brings in serious security threats. Even though encrypting medical images before outsourcing using traditional encryption schemes seem to be a feasible solution, that can not support encrypted domain processing. In this paper, we propose an affine Hill cipher based scheme for encrypted domain medical image fusion. The random vectors used in this scheme are carefully designed to preserve the randomness and security properties when operations are performed on the encrypted data. The proposed scheme offers data privacy and supports encrypted domain processing with no additional storage burden at the cloud side and very low computational burden at the healthcare provider side. The security of the proposed scheme is evaluated through extensive cryptanalysis in terms of resistance against various statistical attacks. The performance of the proposed scheme is analyzed by comparing various metrics of encrypted domain MR-CT/PET image fusion results with those of plaintext domain fusion. The values of structural similarity index, normalized correlation coefficient and structural content are 1 and the image quality index is 0.999, which show that the proposed encrypted domain image fusion provides same accuracy levels as that of plaintext domain image fusion.
机译：医学图像的指数增长使医疗行业成为基于云的范式，它具有庞大的存储和高端加工设施。然而，将包含高度敏感数据的医学图像与第三方云服务器带来严重的安全威胁。尽管在使用传统的加密方案之前加密医学图像似乎是一个可行的解决方案，但不能支持加密域处理。在本文中，我们提出了一种基于仿制域医学图像融合的仿射山密码方案。在该方案上使用该方案中使用的随机向量以在对加密数据执行操作时保留随机性和安全性。该方案提供了数据隐私，并支持加密域处理，在云端没有额外的存储负担，并且在医疗保健提供者方面的计算负担非常低。拟议方案的安全通过广泛的密码分析来抵抗各种统计发作。通过将加密域MR-CT / PET图像融合结果的各种度量与明文域融合的那些进行比较来分析所提出的方案的性能。结构相似性指数，归一化相关系数和结构内容的值为1，图像质量指数为0.999，表明所提出的加密域图像融合提供与明文域图像融合相同的精度级别。

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