Paper Info
Title
A New Hyperchaotic 4D-FDHNN System with Four Positive Lyapunov Exponents and Its Application in Image Encryption
Abstract
In this paper, a hyperchaotic four-dimensional fractional discrete Hopfield neural network system (4D-FDHNN) with four positive Lyapunov exponents is proposed. Firstly, the chaotic dynamics' characteristics of the system are verified by analyzing and comparing the iterative trajectory diagram, phase diagram, attractor diagram, 0-1 test, sample entropy, and Lyapunov exponent. Furthermore, a novel image encryption scheme is designed to use the chaotic system as a pseudo-random number generator. In the scenario, the confusion phase using the fractal idea proposes a fractal-like model scrambling method, effectively enhancing the complexity and security of the confusion. For the advanced diffusion phase, we proposed a kind of Hilbert dynamic random diffusion method, synchronously changing the size and location of the pixel values, which improves the efficiency of the encryption algorithm. Finally, simulation results and security analysis experiments show that the proposed encryption algorithm has good efficiency and high security, and can resist common types of attacks.
Year
DOI
Venue
2022
10.3390/e24070900
ENTROPY
Keywords
DocType
Volume
4D-FDHNN, dynamic analysis, fractal-like scrambling, Hilbert curve, dynamic random diffusion, image encryption
Journal
24
Issue
ISSN
Citations 
7
1099-4300
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Zefei Liu100.34
Jinqing Li235.81
Xiaoqiang Di304.39