A Novel Shark Smell Optimization with Paillier Homomorphic Encryption Based Steganography Technique for Cloud Security

Information technology has advanced greatly with cloud computing (CC). Its service-based computing allows it to offer everything as a pay-as-you-go service online. Cloud data transmission was secured by cryptography and steganography. Steganography hides transmission from undesired users, while cryptography encrypts data for security. Steganography secured cloud transmission best. Steganography used digital images as cover elements. Several time- and frequency-domain image steganography methods are described in the literature. For cloud security, this study develops SSOPHE-ST, a novel shark smell optimization with paillier homomorphic encryption. Before embedding, the PHE algorithm encrypts hidden images in the SSOPHE-ST approach. The SSO algorithm optimises key generation to improve PHE performance. Steganography pixel selection employed search and rescue optimization (SRO). Images are extracted from the embedded image on the cloud server. SSOPHE-ST is tested on different photos, and other aspects are examined afterward. Comparative research showed that SSOPHE-ST outperformed other modern methods.