Journal of Machine and Computing


Secure Medical Image Encryption Using Random Shuffling and Cryptography



Journal of Machine and Computing

Received On : 15 April 2024

Revised On : 28 August 2024

Accepted On : 14 October 2024

Volume 05, Issue 01


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Abstract


Medical image security is a critical concern in healthcare systems due to the sensitive nature of the data involved. This work presents a scheme that combines cryptographic techniques and other methods to prevent medical images from being compromised. The proposed scheme utilizes the inherent unpredictability of chaotic systems to randomly shuffle image pixels, which significantly improves the diffusion properties of the encryption process. This proposed algorithmic method protects against various types of intruders by saving the given image. Simulation output shows that existing work methods get greater levels of protection, efficiency, and robustness, making them suitable for practical applications in medical data protection. Comprehensive analysis validates the encryption scheme's effectiveness, including key sensitivity, statistical measures, and resistance to common cryptographic attacks, demonstrating its potential as a reliable solution for securing medical images.


Keywords


Encryption, Decryption, Symmetric Key, Ergodicity, Cryptography, Random Shuffling, Pixel Modification.


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We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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Cite this article


Attili Venkata Ramana, Vignesh M, Srinivasan R, Vishnupriya Borra, Senthilkumaran B and Desidi Narsimha Reddy, “Secure Medical Image Encryption Using Random Shuffling and Cryptography”, Journal of Machine and Computing. doi: 10.53759/7669/jmc202505009.


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© 2025 Attili Venkata Ramana, Vignesh M, Srinivasan R, Vishnupriya Borra, Senthilkumaran B and Desidi Narsimha Reddy. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.