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Neural Computing and Applications

, Volume 31, Issue 1, pp 219–237 | Cite as

A novel image encryption scheme based on DNA sequence operations and chaotic systems

  • Xiuli ChaiEmail author
  • Zhihua GanEmail author
  • Ke Yuan
  • Yiran Chen
  • Xianxing Liu
Original Article

Abstract

In the paper, a novel image encryption algorithm based on DNA sequence operations and chaotic systems is proposed. The encryption architecture of permutation and diffusion is adopted. Firstly, 256-bit hash value of the plain image is gotten to calculate the initial values and system parameters of the 2D Logistic-adjusted-Sine map (2D-LASM) and a new 1D chaotic system; thus, the encryption scheme highly depends on the original image. Next, the chaotic sequences from 2D-LASM are used to produce the DNA encoding/decoding rule matrix, and the plain image is encoded into a DNA matrix according to it. Thirdly, DNA level row permutation and column permutation are performed on the DNA matrix of the original image, inter-DNA-plane permutation and intra-DNA-plane permutation can be attained simultaneously, and then, DNA XOR operation is performed on the permutated DNA matrix using a DNA key matrix, and the key matrix is produced by the combination of two 1D chaotic systems. Finally, after decoding the confused DNA matrix, the cipher image is obtained. Experimental results and security analyses demonstrate that the proposed scheme not only has good encryption effect, but also is secure enough to resist against the known attacks.

Keywords

Image encryption DNA encoding DNA sequence operation Chaotic system 2D-LASM 

Notes

Acknowledgements

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. 41571417 and U1604145), Natural Science Foundation of the United States (Grant No. CNS-1253424 and ECCS-1202225), Science and Technology Foundation of Henan Province of China (Grant No. 152102210048), Foundation and Frontier Project of Henan Province of China (Grant No. 162300410196), China Postdoctoral Science Foundation (Grant No. 2016M602235), Natural Science Foundation of Educational Committee of Henan Province of China (Grant No. 14A413015), and the Research Foundation of Henan University (Grant No. xxjc20140006).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  1. 1.Institute of Image Processing and Pattern RecognitionHenan UniversityKaifengChina
  2. 2.Department of Electrical and Computer EngineeringDuke UniversityDurhamUSA
  3. 3.School of SoftwareHenan UniversityKaifengChina

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