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ALCencryption: A Secure and Efficient Algorithm for Medical Image Encryption

Jiao Ge1,2,*

1 College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China
2 Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China

* Corresponding Author: Jiao Ge. Email: email

(This article belongs to the Special Issue: Computer Methods in Bio-mechanics and Biomedical Engineering)

Computer Modeling in Engineering & Sciences 2020, 125(3), 1083-1100.


With the rapid development of medical informatization and the popularization of digital imaging equipment, DICOM images contain the personal privacy of patients, and there are security risks in the process of storage and transmission, so it needs to be encrypted. In order to solve the security problem of medical images on mobile devices, a safe and efficient medical image encryption algorithm called ALCencryption is designed. The algorithm first analyzes the medical image and distinguishes the color image from the gray image. For gray images, the improved Arnold map is used to scramble them according to the optimal number of iterations, and then the diffusion is realized by the Logistic and Chebyshev map cross-diffusion algorithm. The color image is encrypted by cross-diffusion algorithm of double chaotic map. Security and efficiency analysis show that the ALCencryption algorithm has the characteristics of small neighboring pixels, large key space, strong key sensitivity, high safety and short encryption time. It is suitable for medical image encryption of mobile devices with high real-time requirements.


Cite This Article

APA Style
Ge, J. (2020). Alcencryption: A secure and efficient algorithm for medical image encryption. Computer Modeling in Engineering & Sciences, 125(3), 1083-1100.
Vancouver Style
Ge J. Alcencryption: A secure and efficient algorithm for medical image encryption. Comput Model Eng Sci. 2020;125(3):1083-1100
IEEE Style
J. Ge, "ALCencryption: A Secure and Efficient Algorithm for Medical Image Encryption," Comput. Model. Eng. Sci., vol. 125, no. 3, pp. 1083-1100. 2020.


cc 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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