Enhanced Diffusion and Confusion Based Encryption Algorithm Using Differential Evolution and Chaotic Mapping

Abstract

Encryption is critical to protecting sensitive data, especially images, against potential illegal access and breaches. The use of chaotic maps for image encryption is widespread among researchers. However, it is necessary to set up initial parameters for chaotic maps to generate random sequences. These parameters need to be selected with care. To determine the optimal initial parameters for image encryption, evolutionary optimization techniques have been used. In this paper, we propose a secure image-based communication system based on an optimized image encryption algorithm. This approach uses differential evolution optimization, which is an ideal solution for reducing convergence time when optimizing chaotic map parameters. Furthermore, the security parameters of these techniques are evaluated, including entropy, Number of Pixel Change Rate (NPCR), Unified Average Changed Intensity (UACI), and correlation coefficients. The simulation results of the proposed encryption approach by combining Arnold’s cat map, chaotic logistic map and optimization method show that the encrypted image is safe against attacks.