Abstract

In the 21st century, an innovative method is the online medical integrated system. It has significant applications, such as reducing the expense of the healthcare system, enhancing the efficacy of the hospital management system, and improving the effectiveness of human capital. The online medical system can undoubtedly play a critical role in the COVID-19 pandemic scenario, and it does as well. A road map of the secured acquisition of medical data from COVID-19 patients, encoding, and distribution to the cloud will be seen in this article. The major aim of this paper is to design a framework for protecting cloud medical data where resources are very limited. Blowfish and Elliptic-curve hybrid cryptographic techniques have been used for encryption. Using the 2D Discrete Wavelet Transform (DWT) method at the fog layer of the cloud, the encrypted data is then embedded into a stego-image format. For a stego-image, the distortion of the cover image must be left unnoticeable. The PSNR, MSE, and SSIM values are most important for maintaining this hiding capacity. The PSNR value differed from 53.08 to 60.36, while the MSE value varied from 0.06 to 0.31 with different data sizes with respect to different formats of the grayscale cover image. For all experimental conditions, the Structural Similarity Index Test (SSIM) values were 1. The proposed model with its stego image PSNR, MSE, and SSIM values has demonstrated that this proposed model can be a suitable substitute to secure medical data in cloud.

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