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AI-Powered Image Security: Utilizing Autoencoders for Advanced Medical Image Encryption

Fehaid Alqahtani*

Department of Computer Science, King Fahad Naval Academy, Al Jubail, 35512, Saudi Arabia

* Corresponding Author: Fehaid Alqahtani. Email: email

(This article belongs to the Special Issue: Emerging Technologies in Information Security )

Computer Modeling in Engineering & Sciences 2024, 141(2), 1709-1724. https://doi.org/10.32604/cmes.2024.054976

Abstract

With the rapid advancement in artificial intelligence (AI) and its application in the Internet of Things (IoT), intelligent technologies are being introduced in the medical field, giving rise to smart healthcare systems. The medical imaging data contains sensitive information, which can easily be stolen or tampered with, necessitating secure encryption schemes designed specifically to protect these images. This paper introduces an artificial intelligence-driven novel encryption scheme tailored for the secure transmission and storage of high-resolution medical images. The proposed scheme utilizes an artificial intelligence-based autoencoder to compress high-resolution medical images and to facilitate fast encryption and decryption. The proposed autoencoder retains important diagnostic information even after reducing the image dimensions. The low-resolution images then undergo a four-stage encryption process. The first two encryption stages involve permutation and the next two stages involve confusion. The first two stages ensure the disruption of the structure of the image, making it secure against statistical attacks. Whereas the two stages of confusion ensure the effective concealment of the pixel values making it difficult to decrypt without secret keys. This encrypted image is then safe for storage or transmission. The proposed scheme has been extensively evaluated against various attacks and statistical security parameters confirming its effectiveness in securing medical image data.

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Cite This Article

APA Style
Alqahtani, F. (2024). Ai-powered image security: utilizing autoencoders for advanced medical image encryption. Computer Modeling in Engineering & Sciences, 141(2), 1709-1724. https://doi.org/10.32604/cmes.2024.054976
Vancouver Style
Alqahtani F. Ai-powered image security: utilizing autoencoders for advanced medical image encryption. Comput Model Eng Sci. 2024;141(2):1709-1724 https://doi.org/10.32604/cmes.2024.054976
IEEE Style
F. Alqahtani, "AI-Powered Image Security: Utilizing Autoencoders for Advanced Medical Image Encryption," Comput. Model. Eng. Sci., vol. 141, no. 2, pp. 1709-1724. 2024. https://doi.org/10.32604/cmes.2024.054976



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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