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Secure data sharing is crucial for protecting sensitive information, and the use of cryptographic protocols, such as the Secure Shell (SSH) protocol, provides an efficient way to achieve this. Found a novel proposed authentication system that combines cryptography and machine learning techniques to ensure secure data sharing within a federated cloud services environment. Their approach involves mutual authentication to establish trust between cooperating entities, threat detection using machine learning algorithms, and cryptography-based key agreement for secure data exchange. They evaluated different classifiers and found that LR, KNN, and DT achieved higher accuracy in malware prediction. Founded another approach where a data-sharing scheme for cloud storage that emphasizes security and efficiency. They introduced a secure cloud storage model utilizing a semi-trusted third party (STTP) for user management, key management, and data processing. By combining a hybrid encryption scheme with a re-encryption protocol, they ensured data confidentiality, unforgeability, and user-centricity. These studies highlight the importance of cryptography in secure data sharing and propose innovative techniques to enhance security and efficiency in data sharing.