Back to Search Start Over

Image encryption algorithm based on Tent-Dynamics coupled map lattices and diffusion of Household.

Authors :
Wang, Xingyuan
Xue, Wenhua
An, Jubai
Source :
Chaos, Solitons & Fractals. Dec2020, Vol. 141, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

• A new spatiotemporal chaotic system is proposed: Tent-Dynamics Coupled Map Lattices chaotic system. • Experimental tests prove that the performance of the Tent-Dynamics Coupled Map Lattices model is better than the traditional coupled mapping lattice model. • Applying the Household method to the diffusion process of image matrix. • The security analysis experiment proves that the image encryption algorithm based on Tent-Dynamics Coupled Map Lattices and diffusion of Household has good performance. This paper presents an image encryption algorithm based on Tent-Dynamics Coupled Map Lattices (TDCML) system and diffusion of Household. All aspects of the TDCML spatiotemporal chaotic system proposed in this paper meet the cryptographic characteristics and are suitable for studying image encryption. The specific image encryption algorithm first generates chaotic sequences according to the TDCML system. The image scrambling uses a cyclic shift algorithm, and the movement of each row and column is determined by the chaotic sequence. Then the image diffusion is improved according to the Household orthogonal decomposition method. Think of each column of the image matrix as a row vector, and then operate according to part of the formulas in the Household transformation to obtain a new row vector. Finally, perform the bitwise XOR operation with the specified chaotic sequence to obtain the final encrypted image. Theoretical analysis and experimental results have proved the security of this encryption algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09600779
Volume :
141
Database :
Academic Search Index
Journal :
Chaos, Solitons & Fractals
Publication Type :
Periodical
Accession number :
147318090
Full Text :
https://doi.org/10.1016/j.chaos.2020.110309