A Medical Image Encryption Algorithm Based on Hermite Chaotic Neural Network
Abstract
To ensure the safety and reliability of medical image during information transmission, a medical image encryption algorithm based on Hermite chaotic neural network is proposed. Firstly, the medical image encryption algorithm uses chaotic sequences generated by the logistic map. Secondly, this chaotic sequence is used to train a Hermite chaotic neural network. Finally, the medical image is encrypted by two key streams generated by the trained Hermite chaotic neural network. Experimental results show that the encryption algorithm is very effective. The security analysis shows that the encryption algorithm can effectively resist statistical analysis, has strong key sensitivity, large keyspace, and greatly improves the security of medical images.
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Neural networks with chaotic behaviors can be used to generate chaotic sequences, which can be used as keys, input parameters, or to diffuse the image.
“Furthermore, neural networks with chaotic behaviors [37] can be used to generate chaotic sequences, which can be used as keys, input parameters, or to diffuse the image.”
From Image Encryption Algorithms: A Survey of Design and Evaluation Metrics (2024) · cites this paper as [37]
Cites
A symmetric image encryption algorithm based on mixed linear–nonlinear coupled map lattice
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Image scrambling encryption algorithm of pixel bit based on chaos map
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A new hyperchaotic map and its application for image encryption
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A new simple one-dimensional chaotic map and its application for image encryption
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Cryptanalysis of image encryption scheme based on a new 1D chaotic system
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Image Encryption Algorithms: A Survey of Design and Evaluation Metrics
Alghamdi, Y., & Munir, A. (2024) · Journal of Cybersecurity and Privacy · doi:10.3390/jcp4010007 · Cited by 98 · see citing works
“Han et al. [37] proposed an image encryption algorithm based on the Hermite chaotic neural network.”
Method
- Authors
- Han, B., Jia, Y., Huang, G., & Cai, L.
- Affiliations
- Chongqing Medical University (CN)
- Venue
- 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)
- Publisher
- IEEE
- Published
- 2020-06
- Pages
- 2644-2648
- OpenAlex
- W3023298866
- Cited by
- 25
- References
- 8
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 8 · 2022: 8 · 2021: 4 · 2020: 1
- FWCI
- 1.62
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
- Physical Sciences › Computer Science › Artificial Intelligence › Computer Science and Engineering
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Keywords
- medical image encryption, logistic map, chaotic sequences, keystream, key sensitivity, medical image security
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