Improvement of Digital Data Security by The Application of Elliptic Curve Cryptography and Butterfly Genetic Algorithm

Abstract

Digital advancements have significantly increased comfort in various technical and non-technical fields. In this era, digital images are widely used in authentication systems, making the security of such images a critical concern. This paper proposes an innovative image security model that focuses on protecting an embedded secret signature in the low-frequency regions of digital images. The model employs Elliptic Curve Cryptography (ECC) for strong encryption and uses the Butterfly Genetic Algorithm (BGA) to enhance security by optimizing the embedding process. The use of the BGA improves robustness against spatial attacks by efficiently shuffling and embedding the image data. Experimentation on a standard image dataset demonstrates that the proposed model achieves superior PSNR and SNR values when compared to existing image security techniques, thereby enhancing both image quality and security.