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A Novel Multi-Channel Image Encryption Algorithm Leveraging Pixel Reorganization and Hyperchaotic Maps

Author

Listed:
  • Wei Feng

    (School of Mathematics and Computer Science, Panzhihua University, Panzhihua 617000, China)

  • Jiaxin Yang

    (School of Mathematics and Computer Science, Panzhihua University, Panzhihua 617000, China)

  • Xiangyu Zhao

    (School of Electrical and Information Engineering, Panzhihua University, Panzhihua 617000, China)

  • Zhentao Qin

    (School of Mathematics and Computer Science, Panzhihua University, Panzhihua 617000, China)

  • Jing Zhang

    (School of Mathematics and Computer Science, Panzhihua University, Panzhihua 617000, China)

  • Zhengguo Zhu

    (School of Mathematics and Computer Science, Panzhihua University, Panzhihua 617000, China)

  • Heping Wen

    (School of Electronic Information, Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China)

  • Kun Qian

    (Key Laboratory of Hunan Province on Information Photonics and Freespace Optical Communications, Hunan Institute of Science and Technology, Yueyang 414006, China
    College of Physics and Electronics, Hunan Institute of Science and Technology, Yueyang 414006, China)

Abstract

Chaos-based encryption is promising for safeguarding digital images. Nonetheless, existing chaos-based encryption algorithms still exhibit certain shortcomings. Given this, we propose a novel multi-channel image encryption algorithm that leverages pixel reorganization and hyperchaotic maps (MIEA-PRHM). Our MIEA-PRHM algorithm employs two hyperchaotic maps to jointly generate chaotic sequences, ensuring a larger key space and better randomness. During the encryption process, we first convert input images into two fused matrices through pixel reorganization. Then, we apply two rounds of scrambling and diffusion operations, coupled with one round of substitution operations, to the high 4-bit matrix. For the low 4-bit matrix, we conduct one round of substitution and diffusion operations. Extensive experiments and comparisons demonstrate that MIEA-PRHM outperforms many recent encryption algorithms in various aspects, especially in encryption efficiency.

Suggested Citation

  • Wei Feng & Jiaxin Yang & Xiangyu Zhao & Zhentao Qin & Jing Zhang & Zhengguo Zhu & Heping Wen & Kun Qian, 2024. "A Novel Multi-Channel Image Encryption Algorithm Leveraging Pixel Reorganization and Hyperchaotic Maps," Mathematics, MDPI, vol. 12(24), pages 1-26, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:24:p:3917-:d:1542198
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    References listed on IDEAS

    as
    1. Erkan, Uğur & Toktas, Abdurrahim & Lai, Qiang, 2023. "Design of two dimensional hyperchaotic system through optimization benchmark function," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. SaberiKamarposhti, Morteza & Ghorbani, Amirabbas & Yadollahi, Mehdi, 2024. "A comprehensive survey on image encryption: Taxonomy, challenges, and future directions," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    3. Lai, Qiang & Lai, Cong & Zhang, Hui & Li, Chunbiao, 2022. "Hidden coexisting hyperchaos of new memristive neuron model and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    4. Li, Yongxin & Li, Chunbiao & Li, Yaning & Moroz, Irene & Yang, Yong, 2024. "A joint image encryption based on a memristive Rulkov neuron with controllable multistability and compressive sensing," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    5. Ren, Lujie & Mou, Jun & Banerjee, Santo & Zhang, Yushu, 2023. "A hyperchaotic map with a new discrete memristor model: Design, dynamical analysis, implementation and application," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
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    Cited by:

    1. J. Alberto Conejero & Carlos Lizama & David Quijada, 2025. "Dynamical Properties for a Unified Class of One-Dimensional Discrete Maps," Mathematics, MDPI, vol. 13(3), pages 1-17, February.

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