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Security and Communication Networks
Volume 2018, Article ID 9803519, 12 pages
Research Article

Meaningful Image Encryption Based on Reversible Data Hiding in Compressive Sensing Domain

1College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China
2School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
3China National Digital Switching System Engineering and Technological R&D Center, Zhengzhou 450002, China
4College of Computer Science, Chongqing University, Chongqing 400044, China
5Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China
6Beijing Advanced Innovation Center for Big Date-Based Precision Medicine, Beihang University, Beijing 100083, China

Correspondence should be addressed to Yang Li; nc.ude.aaub@gnayil

Received 24 July 2017; Revised 10 October 2017; Accepted 16 January 2018; Published 14 February 2018

Academic Editor: Bruce M. Kapron

Copyright © 2018 Ming Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A novel method of meaningful image encryption is proposed in this paper. A secret image is encrypted into another meaningful image using the algorithm of reversible data hiding (RDH). High covertness can be ensured during the communication, and the possibility of being attacked of the secret image would be reduced to a very low level. The key innovation of the proposed method is that RDH is applied to compressive sensing (CS) domain, which brings a variety of benefits in terms of image sampling, communication and security. The secret image after preliminary encryption is embedded into the sparse representation coefficients of the host image with the help of the dictionary. The embedding rate could reach 2 bpp, which is significantly higher than those of other state-of-art schemes. In addition, the computational complexity of receiver is reduced. Simulations verify our proposal.