Parallel strength Pareto evolutionary algorithm-II based image encryption

Abstract

In recent years, many image encryption approaches have been proposed on the basis of chaotic maps. The various types of chaotic maps such as one-dimensional and multi-dimensional have been used to generate the secret keys. Chaotic maps require some parameters and value assignment to these parameters is very crucial. Because, poor value assignments may make the chaotic map un-chaotic. Therefore, hyper-parameter tuning of chaotic maps is required. Recently, meta-heuristic based image encryption approaches have been designed by researchers to resolve this issue. However, the majority of the techniques suffer from poor computational speed and stuck in local optima problems. Therefore, in this study, a strength Pareto evolutionary algorithm-II based meta-heuristic approach is proposed to tune the hyper-parameters of the four-dimensional chaotic map. The proposed approach is also implemented in a parallel fashion to enhance the computational speed. The effectiveness of the proposed approach is evaluated through extensive experiments. Comparative analyses show that the proposed approach outperforms the competitive approaches in terms of entropy, NPCR, UACI, and PSNR by 0.9834, 1.0728, 0.9134, and 0.8971%, respectively.