Optimized Two-Dimensional Chaotic Mapping for Enhanced Image Security Using Sea Lion Algorithm

Abstract

With the rapid progression of digital image processing and network communication, information security issues have become ever more outstanding. Image encryption has to turn out to be an imperative research direction. Till now, countless scholars have projected copious image encryption algorithms based on chaos systems. However, the low-dimensional chaotic sequences have the troubles of shortcode period and low accuracy, which cannot assure the algorithm security. Thus, this paper intends to propose an optimized two-dimensional (2D) chaotic mapping (O2DCM) for image encryption. Here, the initial chaotic system parameters are fine-tuned with a new optimization algorithm referred as the average fitness-based Sea Lion optimization algorithm (AF-SLnO), which is an improved version of standard Sea Lion optimization algorithm (SLnO). The chaotic key generation system is nothing but the proposed AF-SLnO attempts to maximize the information entropy model. As a result, optimal initial parameters for the chaotic system can be determined. The security improvement is demonstrated using standard security analysis such as key sensitivity analysis, histogram analysis and adjacent pixel autocorrelation tests.