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Low-cost multiclass-image encryption based on compressive sensing and chaotic system

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Abstract

In this paper, a compressible and low-cost cryptography system is investigated based a new memristor system for Internet of multimedia things to acquire and transmit multiclass-image signals, such as grayscale, color and 3D images (Stereolithography format). Compression sensing is first introduced to solve the limitation of computing and storage resources faced by detectors when sampling data from different scenarios. The batch data after sampling are fused into 3D cubes, and the confusion–diffusion framework is used to encrypt them in 3D space to ensure the privacy of information during transmission. For confusion procedure, a novel technique, like 3D jigsaw puzzles, is designed to improve the efficiency of scrambling. Furthermore, a new nonlinear primitive is proposed based on three-input majority gate , and the non-sequential diffusion path generated by depth-first search is used for diffusion operation. The experimental results and extensive security analysis show that the proposed encryption technique combined with the implementation of 3D space significantly improves the security and efficiency of batch image processing.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This work was supported by Provincial Natural Science Foundation of Liaoning (Grant Nos. 2020-MS-274); National Natural Science Foundation of China (Grant Nos. 62061014). The Basic Scientific Research Projects of Colleges and Universities of Liaoning Province (Grant Nos. LJKZ0545).

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Authors and Affiliations

  1. School of Information Science and Engineering, Dalian polytechnic University, Dalian, 116034, China

    Yuwen Sha, Jun Mou & Yinghong Cao

  2. Department of Mathematical Sciences, Giuseppe Luigi Lagrange, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, Italy

    Santo Banerjee

  3. Department of Mechanical and Manufacturing Engineering, University of Manitoba, Winnipeg, Canada

    Hadi Jahanshahi

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  1. Yuwen Sha
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  2. Jun Mou
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Contributions

Yuwen Sha designed and carried out experiments, data analyzed and manuscript wrote. Ju Mou and Santo Banerjee made the theoretical guidance for this paper. Yinghong Cao and Hadi Jahanshahi carried out experiment and improved the algorithm. All authors reviewed the manuscript.

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Correspondence to Jun Mou.

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Sha, Y., Mou, J., Banerjee, S. et al. Low-cost multiclass-image encryption based on compressive sensing and chaotic system. Nonlinear Dyn 111, 7831–7857 (2023). https://doi.org/10.1007/s11071-022-08206-8

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  • DOI: https://doi.org/10.1007/s11071-022-08206-8

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