Application of Fish-swarm and Genetic Algorithm in Optimization of Chaotic Image Encryntion
Yao Li-sha, XU Guo-ming, Zhao Feng · 2020
The security of digital images has attracted much attention. In order to reduce the correlation of image, increase the key space and improve security, a new image encrytion algorithm based on fish-swarm and genetic algorithm and chaotic function is proposed in this paper. The algorithm applies fish-swarm and genetic algorithm to chaos scrambling images for optimization. Artificial fish-swarm algorithm begins to converge quickly, then has slow convergence. It is insensitive to initial value and can avoid local extremum. It is robust for genetic algorithm. But genetic algorithm is easy to fall into local extremum and sensitive to initial value. This paper proposes to combine artificial fish-swarm algorithm with genetic algorithm and optimize chaotic image encryption algorithm. Firstly, the chaotic function is used to generate multiple encrypted images as the initial fish swarm of the fish swarm algorithm, then the selection, crossover and mutation of genetic algorithm are integrated into the improved artificial fish-swarm algorithm to optimize the chaotic encrypted image iteratively to obtain the best encrypted image. The simulation results and security analysis show that the algorithm has the advantages of low correlation, higher security and stronger ability to resist statistical analysis attacks and differential attacks comparing with other image encrytion algorithms.