A Study of An Image Encryption Model Based on Tent-Ushiki Chaotic Fusion

Abstract

Aiming at the shortcomings of current image encryption, such as simple structure, few parameters and small key space, we propose the Tent-Ushiki chaotic mapping image encryption method based on the improved firefly optimization algorithm. First, a chaotic mapping model based on the fusion of Tent and Ushiki is proposed. Second, for the lack of parameter optimization in chaotic models in general, we introduce the firefly optimization algorithm and optimize the algorithm for the shortcomings in terms of the adaptive step size, the adjustment factor and the inertia weights. Finally, the improved firefly algorithm is used for the fusion of the chaotic parameters of Tent and Ushiki. In the simulation experiments, this paper’s algorithm performs well in the statistical analysis and adjacent element correlation of the classical image test and significantly outperforms the comparative algorithms in terms of information entropy and anti-attack, which demonstrates that the algorithm is able to optimize the image encryption effect better.