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A Block Compressed Sensing for Images Selective Encryption in Cloud

Xingting Liu1, Jianming Zhang2,*, Xudong Li2, Siwang Zhou1, Siyuan Zhou2, Hye-JinKim3

College of Computer Science and Electrical Engineering, Hunan University, Changsha, 410082, China.
School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, 410114, China.
Business Administration Research Institute, Sungshin W. University, Seoul, 02844, Republic of Korea.

*Corresponding Author: Jianming Zhang. Email: email.

Journal of Cyber Security 2019, 1(1), 29-41.


The theory of compressed sensing (CS) has been proposed to reduce the processing time and accelerate the scanning process. In this paper, the image recovery task is considered to outsource to the cloud server for its abundant computing and storage resources. However, the cloud server is untrusted then may pose a considerable amount of concern for potential privacy leakage. How to protect data privacy and simultaneously maintain management of the image remains challenging. Motivated by the above challenge, we propose an image encryption algorithm based on chaotic system, CS and image saliency. In our scheme, we outsource the image CS samples to cloud for reduced storage and portable computing. Consider privacy, the scheme ensures the cloud to securely reconstruct image. Theoretical analysis and experiment show the scheme achieves effectiveness, efficiency and high security simultaneously.


Cite This Article

X. Liu, J. Zhang, X. Li, S. Zhou, S. Zhou et al., "A block compressed sensing for images selective encryption in cloud," Journal of Cyber Security, vol. 1, no.1, pp. 29–41, 2019.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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