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A K-SVD Based Compressive Sensing Method for Visual Chaotic Image Encryption

Author

Listed:
  • Zizhao Xie

    (School of Information Management, Jiangxi University of Finance and Economics, Nanchang 330013, China)

  • Jingru Sun

    (College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China
    Chongqing Research Institute, Hunan University, Chongqing 401120, China)

  • Yiping Tang

    (College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China)

  • Xin Tang

    (College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China)

  • Oluyomi Simpson

    (School of Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK)

  • Yichuang Sun

    (School of Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK)

Abstract

The visually secure image encryption scheme is an effective image encryption method, which embeds an encrypted image into a visual image to realize a secure and secret image transfer. This paper proposes a merging compression and encryption chaos image visual encryption scheme. First, a dictionary matrix D is constructed with the plain image by the K-SVD algorithm, which can encrypt the image while sparsing. Second, an improved Zeraoulia-Sprott chaotic map and logistic map are employed to generate three S-Boxes, which are used to complete scrambling, diffusion, and embedding operations. The secret keys of this scheme contain the initial value of the chaotic system and the dictionary matrix D, which significantly increases the key space, plain image correlation, and system security. Simulation shows the proposed image encryption scheme can resist most attacks and, compared with the existing scheme, the proposed scheme has a larger key space, higher plain image correlation, and better image restoration quality, improving image encryption processing efficiency and security.

Suggested Citation

  • Zizhao Xie & Jingru Sun & Yiping Tang & Xin Tang & Oluyomi Simpson & Yichuang Sun, 2023. "A K-SVD Based Compressive Sensing Method for Visual Chaotic Image Encryption," Mathematics, MDPI, vol. 11(7), pages 1-20, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1658-:d:1111622
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    References listed on IDEAS

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    1. Wang, Mengjiao & Liao, Xiaohan & Deng, Yong & Li, Zhijun & Su, Yongxin & Zeng, Yicheng, 2020. "Dynamics, synchronization and circuit implementation of a simple fractional-order chaotic system with hidden attractors," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    2. Yu, Fei & Shen, Hui & Zhang, Zinan & Huang, Yuanyuan & Cai, Shuo & Du, Sichun, 2021. "Dynamics analysis, hardware implementation and engineering applications of novel multi-style attractors in a neural network under electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    3. Jingru Sun & Mu Peng & Fang Liu & Cong Tang, 2020. "Protecting Compressive Ghost Imaging with Hyperchaotic System and DNA Encoding," Complexity, Hindawi, vol. 2020, pages 1-13, October.
    4. Xiaoyuan Wang & Xinrui Zhang & Meng Gao & Yuanze Tian & Chunhua Wang & Herbert Ho-Ching Iu, 2023. "A Color Image Encryption Algorithm Based on Hash Table, Hilbert Curve and Hyper-Chaotic Synchronization," Mathematics, MDPI, vol. 11(3), pages 1-18, January.
    5. Hairong Lin & Chunhua Wang & Fei Yu & Jingru Sun & Sichun Du & Zekun Deng & Quanli Deng, 2023. "A Review of Chaotic Systems Based on Memristive Hopfield Neural Networks," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
    6. Dejian Fang & Shuliang Sun, 2020. "A new secure image encryption algorithm based on a 5D hyperchaotic map," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-13, November.
    7. Yue Zhu & Chunhua Wang & Jingru Sun & Fei Yu, 2023. "A Chaotic Image Encryption Method Based on the Artificial Fish Swarms Algorithm and the DNA Coding," Mathematics, MDPI, vol. 11(3), pages 1-18, February.
    8. P. Chinnasamy & P. Deepalakshmi & Ashit Kumar Dutta & Jinsang You & Gyanendra Prasad Joshi, 2021. "Ciphertext-Policy Attribute-Based Encryption for Cloud Storage: Toward Data Privacy and Authentication in AI-Enabled IoT System," Mathematics, MDPI, vol. 10(1), pages 1-24, December.
    9. Lin, Hairong & Wang, Chunhua & Sun, Jingru & Zhang, Xin & Sun, Yichuang & Iu, Herbert H.C., 2023. "Memristor-coupled asymmetric neural networks: Bionic modeling, chaotic dynamics analysis and encryption application," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
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    Cited by:

    1. Amir Rezaie & Saleh Mobayen & Mohammad Reza Ghaemi & Afef Fekih & Anton Zhilenkov, 2023. "Design of a Fixed-Time Stabilizer for Uncertain Chaotic Systems Subject to External Disturbances," Mathematics, MDPI, vol. 11(15), pages 1-14, July.
    2. Mengyao Li & Xianwen Fang & Asimeng Ernest, 2023. "A Color Image Encryption Method Based on Dynamic Selection Chaotic System and Singular Value Decomposition," Mathematics, MDPI, vol. 11(15), pages 1-27, July.
    3. Qingye Huang & Linqing Huang & Shuting Cai & Xiaoming Xiong & Hui Zhang, 2023. "On a Symmetric Image Cryptosystem Based on a Novel One-Dimensional Chaotic System and Banyan Network," Mathematics, MDPI, vol. 11(21), pages 1-21, October.

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