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Image encryption algorithm based on cross-scrambling and rapid-mode diffusion

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Abstract

An efficient encryption algorithm largely depends on the chaotic performance of chaotic map. The stronger the chaotic performance of chaotic map, the higher the security of the algorithm. For the purpose of improving the chaotic performance, we put forward a novel two-dimensional Sine-embedded-coupling map (2D-SECM) in this paper. By comparing with other 2D chaotic maps, 2D-SECM has more excellent pseudo-random characteristics, unpredictability, and wider range of chaos. For the purpose of studying its application, we put forward an image encryption approach based on 2D-SECM (SECM-IEA). SECM-IEA includes bit-level scrambling based on cross-transform and a round of fast diffusion processing. Simulation experiment and security evaluation reveal that SECM-IEA can resist common types of attacks and has more excellent security than some algorithms. It is demonstrated that SECM has better chaotic performance from the perspective of encryption performance.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (No: 61672124), the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (No: MMJJ20170203), Liaoning Province Science and Technology Innovation Leading Talents Program Project (No: XLYC1802013), Key R&D Projects of Liaoning Province (No: 2019020105-JH2/103), Jinan City ‘20 universities’ Funding Projects Introducing Innovation Team Program (No: 2019GXRC031), Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (No: MIMS20-M-02).

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Authors and Affiliations

  1. School of Information Science and Technology, Dalian Maritime University, Dalian, 116026, China

    Xingyuan Wang & Xuan Chen

  2. Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, China

    Xingyuan Wang

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  1. Xingyuan Wang
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Wang, X., Chen, X. Image encryption algorithm based on cross-scrambling and rapid-mode diffusion. Vis Comput 39, 5041–5068 (2023). https://doi.org/10.1007/s00371-022-02645-5

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