Mayfly optimization with chaos-based image encryption technique for cloud computing environment

Abstract

Cloud computing (CC) technologies become popular due to their characteristics of maximum availability, flexibility, and scalability. Despite the benefits of CC, security becomes a major challenging issue that can be resolved by the use of image encryption techniques. Numerous works have been carried out with several approaches, and effective models need to be designed to enhance secure image encryption algorithms. Recently, chaotic approaches have been available in various domains, such as design of cryptosystems and image encryption. Chaos-based methods utilize random chaos sequences for image encryption, which are highly secure and fast. In this view, this study introduces a unique mayfly optimization with chaos-based image encryption (MFO-CBIE) technique for CC environment. The major intention of the MFO-CBIE model is to accomplish security in the CC environment via encryption and key generation process. The proposed MFO-CBIE model follows a three-stage process, namely image encryption, optimal key generation, and image decryption. In addition, the MFO-CBIE model employs the MFO algorithm for the optimal key generation process of the chaos-based encryption technique. Once the images are encrypted, they are securely transmitted to the cloud server. On the receiver side, the cipher image gets accessed from the cloud server, and then the decryption process is carried out. The experimental evaluation of the MFO-CBIE model is tested using benchmark images, and the results ensured the promising performance of the MFO-CBIE model over recent approaches.