An image encryption algorithm based on BP neural network and hyperchaotic system
Abstract
To reduce the bandwidth and storage resources of image information in communication transmission, and improve the secure communication of information. In this paper, an image compression and encryption algorithm based on fractional-order memristive hyperchaotic system and BP neural network is proposed. In this algorithm, the image pixel values are compressed by BP neural network, the chaotic sequences of the fractional-order memristive hyperchaotic system are used to diffuse the pixel values. The experimental simulation results indicate that the proposed algorithm not only can effectively compress and encrypt image, but also have better security features. Therefore, this work provides theoretical guidance and experimental basis for the safe transmission and storage of image information in practical communication.
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Neural networks can be used to permute and/or compress plaintext images.
“Neural networks can be used to permute [35] and/or compress the plaintext images [36].”
From Image Encryption Algorithms: A Survey of Design and Evaluation Metrics (2024) · cites this paper as [36]
Cites
Bao, B., Jiang, T., Wang, G., Jin, P., Bao, H., & Chen, M. (2017) · Nonlinear Dynamics · doi:10.1007/s11071-017-3507-0 · Cited by 239 · see citing works
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Image encryption algorithm based on 2D hyperchaotic map
Gao, X. (2021) · Optics & Laser Technology · doi:10.1016/j.optlastec.2021.107252 · Cited by 160 · see citing works
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
“Neural networks can be used to permute [35] and/or compress the plaintext images [36].”
MethodImage encryption algorithm based on improved Zigzag transformation and quaternary DNA coding
Wang, Q., Zhang, X., & Zhao, X. (2022) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2022.103340 · Cited by 35 · see citing works
- Authors
- Yang, F., Mou, J., Cao, Y., & Chu, R.
- Affiliations
- Dalian Polytechnic University (CN)
- Venue
- China Communications
- Published
- 2020-05
- Volume
- 17
- Issue
- 5
- Pages
- 21-28
- ISSN
- 1673-5447 (ISSN-L)
- OpenAlex
- W3029465972
- Cited by
- 65
- References
- 1
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 10 · 2023: 14 · 2022: 22 · 2021: 12 · 2020: 2
- FWCI
- 4.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- China Communications (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 Data Compression Techniques
- Keywords
- image encryption, image compression, BP neural network, hyperchaotic systems, chaotic sequences, pixel diffusion, secure communication, bandwidth reduction
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