Multimedia Tools and Applications

, Volume 77, Issue 20, pp 26191–26217 | Cite as

An efficient and self-adapting colour-image encryption algorithm based on chaos and interactions among multiple layers

  • Yuling Luo
  • Ronglong Zhou
  • Junxiu LiuEmail author
  • Senhui Qiu
  • Yi Cao


In this paper, we propose an efficient and self-adapting colour-image encryption algorithm based on chaos and the interactions among multiple red, green and blue (RGB) layers. Our study uses two chaotic systems and the interactions among the multiple layers to strengthen the cryptosystem for the colour-image encryption, which can achieve better confusion and diffusion performances. In the confusion process, we use the novel Rubik’s Cube Scheme (RCS) to scramble the image. The significant advantage of this approach is that it sufficiently destroys the correlation among the different layers of colour image, which is the most important feature of the randomness for the encryption. The theoretical analysis and experimental results show that the proposed algorithm can improve the encoding efficiency, enhances the security of the cipher-text, has a large key space and high key sensitivity, and is also able to resist statistical and exhaustive attacks.


Colour-image encryption Chaos Interaction of multiple layers Security analysis 



This research was supported by the National Natural Science Foundation of China under Grant 61661008, the Guangxi Natural Science Foundation under Grant 2017GXNSFAA198180, 2015GXNSFBA139256 and 2016GXNSFCA380017, the funding of Overseas 100 Talents Program of Guangxi Higher Education, the Research Project of Guangxi University of China under Grant KY2016YB059, Guangxi Key Lab of Multi-source Information Mining & Security under Grant MIMS15-07, the Doctoral Research Foundation of Guangxi Normal University, the grant from Guangxi Experiment Centre of Information Science, and the Innovation Project of Guangxi Graduate Education under Grant YCSZ2017055.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Guangxi Key Lab of Multi-Source Information Mining and Security, Faculty of Electronic EngineeringGuangxi Normal UniversityGuilinChina
  2. 2.Guangxi Experiment Centre of Information ScienceGuilinChina
  3. 3.Department of Business Transformation and Sustainable Enterprise, Surrey Business School, University of SurreySurreyUK

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