A novel image encryption algorithm based on fractional order 5D cellular neural network and Fisher-Yates scrambling
Xingyuan Wang,
Yining Su,
Chao Luo and
Chunpeng Wang
PLOS ONE, 2020, vol. 15, issue 7, 1-18
Abstract:
This paper proposes a new chaotic image encryption algorithm. Firstly, an original phased composite chaotic map is used. The comparative study shows that the map cryptographic characteristics are better than the Logistic map, and the map is used as the controller of Fisher-Yates scrambling. Secondly, with the higher complexity of the fractional-order five-dimensional cellular neural network system, it is used as a diffusion controller in the encryption process. And mix the secret key, mapping and plaintext, we can obtain the final ciphertext. Finally, the comparative experiments prove that the proposed algorithm improves the encryption efficiency, has good security performance, and can resist common attack methods.
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236015 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 36015&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0236015
DOI: 10.1371/journal.pone.0236015
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().