An Image Encryption Model Using Hyper Chaotic Map Dependent Grey-Intelligent Optimization

With the rapid growth of technologies and scientific innovations, information sharing was made digital, like text messages, file sharing, and pictures and audio messages especially, digital images have been found widely in economics, politics, education, and some other important fields. Methods to securely as well as secretly transmit and store digital images, particularly those that contain private information, have thus become an important concern in those domains. Image encryption technology is one to ensure the safety of image information, as it provides a pattern that is effective for people in transferring and receiving securely over a network. In this research, the Hyperchaotic map image encryption algorithm is proposed based on Grey-intelligent optimization. The optimal range of chaotic parameters in the model offers the secret image excellent security as well as with hyper-hybrid mapping, chaos encryption is used to encrypt the secret image. The proposed method achieved an improvement of 18.08% for MSE, 3.47% for PSNR, 18.55% for RMSE, and 0.33% for SSIM, demonstrating the model's efficacy and excellence of the research.