Investigating Effect of Optimization Algorithms on Chaos Based Image Encryption

Image encryption is a specialized subfield of cryptography, distinguished by the high correlation between neighboring pixels, which necessitates unique approaches to disrupt this correlation. While all encryption approaches fundamentally involve confusion and diffusion operators, the specific implementations of these operators can vary significantly. In recent years, approaches that combine chaos theory with optimization techniques, which aim to find the optimal solution among numerous possibilities, have become prevalent. These studies, which aim to enhance the security and efficiency of the encryption process, such as by selecting the initial values of chaotic maps in regions with high chaotic behavior, show promise. This study examines the most commonly applied optimization methods in the field of cryptography within the context of image encryption, providing a comprehensive overview. Additionally, it empirically demonstrates that the optimization techniques employed in image encryption studies improve encryption quality.