Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

A Novel Hybrid Algorithm Based on Fibonacci p-code and Gray DES

Authors
Guangming Yang, Jian Xiao, Zhenhua Tan, Wei Cheng
Corresponding Author
Guangming Yang
Available Online June 2017.
DOI
10.2991/caai-17.2017.68How to use a DOI?
Keywords
gray DES; fibonacci p-code; data encryption; frequency domain scrambling
Abstract

In this paper, a novel hybrid algorithm is proposed to solve the security problem of image information, which is on the basis of gray DES algorithm and Fibonacci p-code algorithm. Then, using self-reverse matrix to improve the Fibonacci p-code encryption algorithm and combing it with Gray DES algorithm to proposes a new image encryption algorithm, in order to reduce image distortion. Finally, the paper evaluated the proposed hybrid algorithm's performance through statistical analysis and diffusion tests. As a result, the system is more robust against the JPEG compression method and can be compatible with the international universal compression method.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
10.2991/caai-17.2017.68How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Guangming Yang
AU  - Jian Xiao
AU  - Zhenhua Tan
AU  - Wei Cheng
PY  - 2017/06
DA  - 2017/06
TI  - A Novel Hybrid Algorithm Based on Fibonacci p-code and Gray DES
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 300
EP  - 303
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.68
DO  - 10.2991/caai-17.2017.68
ID  - Yang2017/06
ER  -