Image Encryption Method Based On Metaheuristic Social Group Optimization Algorithm

The multimedia data exchange has been raised due to rapid technological improvements in recent years. The attackers investigate how to acquire this data so they can obtain people’s sensitive information. Thus, in the present scenario, security is a big concern. Therefore, we have presented a novel image encryption (IE) method based on the metaheuristic social group optimization (SGO) algorithm that explores the best parameter value of the chaotic maps for better security. In the proposed method, the 1-D chaotic logistic map (CLM) is employed for optimal key generation and substitution box (s-box), whereas the 1-D chaotic tent map (CTM) is employed to generate an optimal shuffling index to achieve permutation in the encryption method. In the proposed method, there are a total four stages to achieve the encryption. In the first and last stages, the optimal random key is employed to perform an exclusive-OR operation, whereas in the second and third stages, s-box and permutation are performed. Next, the demonstration of the presented IE method is done for the standard dataset images by analyzing the various security parameters. Lastly, the effectiveness of the proposed approach is compared to existing IE methods using these parameters. The result indicates that the proposed method achieves an average entropy value of 7.9971, an NPCR value of 99.607, and a PSNR value of 14.026dB.