Hybrid Visual and Optimal Elliptic Curve Cryptography for Medical Image Security in Iot
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Abstract
In this manuscript, a hybridizing visual cryptography with Optimal Elliptic Curve Cryptography is proposed for medical image security in Internet of Things (IoT). The visual cryptography is generally used to send the secure and confidential medical image to the receiver. Here, the medical image is transmitted as shares and all shares of the medical image are collectively loaded to retrieve the original medical image. Moreover, the multiple shares are created interms of pixel values of medical image and this share is extracted and partioned in blocks. The blocks of every share are encrypted with elliptic curve cryptography (ECC) mechanisms and encrypted image is decrypted using ECC decrypts. In hybridizing visual crypto with optimal elliptic curve crypto, the optimal key will be generated using an imperialist competitive algorithm. Finally, the decrypted output image compares to the original image. The proposed system is executed on MATLAB platform and performance is evaluated with existing method like Score-based Key Enumeration Algorithm (SKEA). The proposed ESEA approach reduces the file size as 45.76%, 24.97%, 15.86%, 33% and 33.86%.And higher PSNR as 29.08%, 25.86%, 23.98%, 25.86% and 42.75%. The proposed ESEA approach achieves 6.89% higher security than existing SKEA method. Furthermore, the simulation outcome demonstrates that the proposed technique can be able to find the optimal global solutions efficiently and accurately than the existing techniques.
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