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A novel compressive sensing-based framework for image compression-encryption with S-box

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Abstract

In this paper, we find that compressive sensing (CS) with the chaotic measurement matrix has a strong sensitivity to plaintext. Because of the quantification executed after CS, however, the plaintext sensitivity produced by CS may be weakened greatly. Thus, we propose a novel CS-based compression-encryption framework (CS-CEF) using the intrinsic property of CS to provide a strong plaintext sensitivity for the compression-encryption scheme, which takes a low additional computation cost. Meanwhile, a simple and efficient Substitution box (S-box) construction algorithm (SbCA) based on chaos is designed. Compared with the existing S-box construction methods, the simulation results prove that the proposed S-box has stronger cryptographic characteristics. Based on the above works, we develop an efficient and secure image compression-encryption scheme using S-box (CSb-CES) under the proposed CS-CEF. The simulations and security analysis illustrate that the proposed CSb-CES has the higher efficiency and security compared with the several state-of-the-art CS-based compression-encryption schemes.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China [grant numbers 61374178, 61402092, 61603082]; the Online Education Research Fund of the MOE Research Center for Online Education, China [qtone education, grant number 2016ZD306]; the Ph.D. Start-Up Foundation of Liaoning Province, China [grant number 201501141]; and the Fundamental Research Funds for the Central Universities [grant number N171704004].

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  1. Software College, Northeastern University, Shenyang, 110819, China

    Zhiliang Zhu, Yanjie Song, Wei Zhang, Hai Yu & Yuli Zhao

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  1. Zhiliang Zhu
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  2. Yanjie Song
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  3. Wei Zhang
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  4. Hai Yu
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Correspondence to Yanjie Song.

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Zhu, Z., Song, Y., Zhang, W. et al. A novel compressive sensing-based framework for image compression-encryption with S-box. Multimed Tools Appl 79, 25497–25533 (2020). https://doi.org/10.1007/s11042-020-09193-x

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