A New V-Net Convolutional Neural Network Based on Four-Dimensional Hyperchaotic System for Medical Image Encryption

Author:

Wang Xiaowei1,Yin Shoulin1,Shafiq Muhammad2ORCID,Laghari Asif Ali3,Karim Shahid4,Cheikhrouhou Omar56ORCID,Alhakami Wajdi7,Hamam Habib8910

Affiliation:

1. Software College, Shenyang Normal University, Shenyang, China

2. Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China

3. Department of Computer Science, Sindh Madressatul Islam University, Karachi, Pakistan

4. Faculty of Science and Technology, ILMA University, Karachi, Pakistan

5. CES Laboratory, National School of Engineers of Sfax, University of Sfax, Sfax 3038, Tunisia

6. Higher Institute of Computer Science of Mahdia, University of Monastir, Mahdia 5111, Tunisia

7. Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia

8. Faculty of Engineering, Moncton University, Moncton, NB E1A3E9, Canada

9. Spectrum of Knowledge Production & Skills Development, Sfax 3027, Tunisia

10. School of Electrical Engineering, Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa

Abstract

In the transmission of medical images, if the image is not processed, it is very likely to leak data and personal privacy, resulting in unpredictable consequences. Traditional encryption algorithms have limited ability to deal with complex data. The chaotic system is characterized by randomness and ergodicity, which has advantages over traditional encryption algorithms in image encryption processing. A novel V-net convolutional neural network (CNN) based on four-dimensional hyperchaotic system for medical image encryption is presented in this study. Firstly, the plaintext medical images are processed into 4D hyperchaotic sequence images, including image segmentation, chaotic system processing, and pseudorandom sequence generation. Then, V-net CNN is used to train chaotic sequences to eliminate the periodicity of chaotic sequences. Finally, the chaotic sequence image is diffused to change the raw image pixel to realize the encryption processing. Simulation test analysis demonstrates that the proposed algorithm has better effect, robustness, and plaintext sensitivity.

Funder

Taif University

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

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