A Harris Hawk Optimization with chaotic map based image encryption for multimedia application

Image security plays a vital role in communication networks. Despite advancements in encryption, securing protective image data remains a computationally challenging problem, requiring the use of a secure environment to secure data transmitted from the device through the network. Encryption is essential for safeguarding essential data against unauthorized access or malfunction, especially for images. The contribution of the proposed model is to provide an analytical hybrid Harris Hawk Optimization (HHO) with a chaotic map approach which can be used to improve the overall performance of standard encryption techniques in image-based encrypted communication. Previously, the algorithm computes numerous chaotic Logistic map and an encrypted images, where the pending plain image calculates the session key for the map’s input parameters. Afterwards, encrypted images are presented as hawks and made to work well with HHO. The optimized ciphered image is expressed as a fitness function using correlation coefficients related to nearby pixels. When compared to existing algorithms, the proposed NPCR (99%), UACI (33%), and entropy (7.97) demonstrate superior performance. The proposed hybrid approach outperforms traditional algorithms in terms of security while preserving image quality.