A Novel Framework for Image Encryption by Integrating Modified Moth Flame Optimization and Logistic Chaotic Map for Enhanced Security
Akshat Aggarwal, Eshaan Awasthi, Deepika Kukreja, Jyoti Kedia, Indu Bala · Research Square · 2024
Abstract Preserving the confidentiality of sensitive image data is of paramount importance in the digital world. Therefore, an optimized image encryption algorithm is proposed in this paper for securing image-based communication. The proposed Modified Moth Flame Optimization Algorithm (MMFO) delved along with a Logistic Chaotic Map is used to obtain improved values of evaluation parameters such as Correlation Coefficient(CC), Image Entropy (IE), Unified Average Changing Intensity (UACI) and Normalized Pixel Change Rate (NPCR) along with Uniform Histograms for the encrypted image that outperforms various state-of-the-art metaheuristic algorithms coupled with diverse chaotic maps. Using multiple plain image-dependent session keys and a Logistic Chaotic map, several encrypted images are generated which act as an initial population for the Modified algorithm. The results are presented to validate the performance of the proposed algorithm. It has been observed that the proposed algorithm has a substantial de-correlation of adjacent pixels in the encrypted image, achieving values on the order of 10−6.