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An efficient meaningful double-image encryption algorithm based on parallel compressive sensing and FRFT embedding

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Abstract

The transmission of images via the Internet has grown exponentially in the past few decades. However, the Internet considered as an insecure method of information transmission may cause serious privacy issues. To overcome such potential security issues, a novel visually meaningful double-image encryption (VMDIE) algorithm conjugating quantum cellular neural network (QCNN), compressive sensing (CS) and fractional Fourier transform (FRFT) is proposed in this paper. First, the wavelet coefficients of two plain images are scrambled by the Fisher-Yates confusion algorithm, and compressed by key-controlled partial Hadamard matrix. The final meaningful cipher image is generated by embedding the encrypted images into a same-scale host image via the FRFT-based embedding approach. Besides, the eigenvalues of plain images are utilized to generate secret key streams to improve the ability of proposed VMDIE algorithm to withstand various plaintext attacks. Afterward, the plaintext eigenvalues are hidden into the alpha channel of meaningful cipher image under control of keys to relieve unnecessary storage space and transmission cost. Ultimately, simulation results and security analyses indicate that the proposed VMDIE algorithm is effective and can withstand multiple attacks.

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Data availability

The image datasets generated and analyzed during the current study are available from the corresponding author upon the reasonable request.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China [Grant No.61701043, 41874140], the Shaanxi Province Science and Technology Program [Grant No.2020JM-220, 2020JQ-351], the Fundamental Research Funds for the Central Universities of China [Grant No.300102240205], the Natural Science Foundation of Fujian Province [Grant No.2020 J05169] and the Natural Science Foundation of Heilongjiang Province [Grant No.F2018022].

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Authors and Affiliations

  1. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510006, China

    Donghua Jiang & Lidong Liu

  2. School of Information Engineering, Chang’an University, Xi’an, China

    Lidong Liu

  3. School of Electrical and Control Engineering, Chang’an University, Xi’an, 710064, China

    Liya Zhu

  4. School of Information Science and Technology, Dalian Maritime University, Da’lian, 116026, China

    Xingyuan Wang

  5. School of Physics and Information Engineering, Minnan Normal University, Zhang’zhou, 363000, China

    Yingpin Chen

  6. Physics and Electronic Engineering School, Harbin Normal University, Harbin, 150025, China

    Xianwei Rong

Authors
  1. Donghua Jiang
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  2. Lidong Liu
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  3. Liya Zhu
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  4. Xingyuan Wang
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  5. Yingpin Chen
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  6. Xianwei Rong
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Correspondence to Lidong Liu.

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Jiang, D., Liu, L., Zhu, L. et al. An efficient meaningful double-image encryption algorithm based on parallel compressive sensing and FRFT embedding. Multimed Tools Appl 82, 27337–27363 (2023). https://doi.org/10.1007/s11042-023-14601-z

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