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Cloud-decryption-assisted image compression and encryption based on compressed sensing

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Abstract

In this paper, we propose a new image compression and encryption scheme (ICES) based on compressed sensing (CS) and double random phase encoding (DRPE), as well as a joint decryption on the cloud and user side. In the encryption, the plain image is firstly decomposed into approximate component and detail components by discrete wavelet transform (DWT), then the approximate component is scrambled, and detail components are compressed using a measurement matrix constructed by the Logistic-tent system. Secondly, the scrambled approximate component and compressed detail components are combined into a complex matrix, and then it is subjected to DRPE to get the amplitude and phase matrices. Subsequently, the resulting matrices are performed random pixel scrambling and diffusion to obtain the final cipher image. During the decryption, the cipher image is first partially decrypted on the cloud, and then fully decrypted to recover the original image on the user side, and we can judge whether the cloud has cheated us by comparing the contour similarity between the approximate component and the detail component returned by the cloud to the user, which not only significantly shortens the decryption time, but also effectively prevents malicious deception of the cloud. Experimental results and performance analyses demonstrate its effectiveness and efficiency.

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Acknowledgments

All the authors are deeply grateful to the editors for smooth and fast handling of the manuscript. The authors would also like to thank the anonymous referees for their valuable suggestions to improve the quality of this paper. This work is supported by the National Natural Science Foundation of China (Grant No. 61802111, 61872125, 61871175), Science and Technology Foundation of Henan Province of China (Grant No. 182102210027, 182102410051), China Postdoctoral Science Foundation (Grant No. 2018 T110723), Key Scientific Research Projects for Colleges and Universities of Henan Province (Grant No. 19A413001), Natural Science Foundation of Henan Province (Grant No. 182300410164), Graduate Education Innovation and Quality Improvement Project of Henan University (Grant No. SYL18020105), Henan Higher Education Teaching Reform Research and Practice Project (Graduate Education) (Grant No. 2019SJGLX080Y), and the Key Science and Technology Project of Henan Province (Grant No. 201300210400, 212102210094).

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Authors and Affiliations

  1. School of Artificial Intelligence, Henan University, Kaifeng, 475004, China

    Jiangyu Fu, Xiuli Chai & Yang Lu

  2. School of Software, Intelligent Data Processing Engineering Research Center of Henan Province, Institute of Intelligent Network System, Henan University, Kaifeng, 475004, China

    Zhihua Gan

  3. Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, 475004, China

    Xiuli Chai & Yang Lu

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  1. Jiangyu Fu
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Fu, J., Gan, Z., Chai, X. et al. Cloud-decryption-assisted image compression and encryption based on compressed sensing. Multimed Tools Appl 81, 17401–17436 (2022). https://doi.org/10.1007/s11042-022-12607-7

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