Open Access

ARTICLE

A Block Compressed Sensing for Images Selective Encryption in Cloud

by Xingting Liu¹, Jianming Zhang², Xudong Li², Siwang Zhou¹, Siyuan Zhou², Hye-JinKim ³

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

*Corresponding Author: Jianming Zhang. Email: .

Journal of Cyber Security 2019, 1(1), 29-41. https://doi.org/10.32604/jcs.2019.06013

Abstract

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.

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Keywords

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