Secure Data Exchange in Cloud Computing: Enhancing Confidentiality, Integrity, and Availability Through Data Partitioning and Encryption

This paper explores advanced encryption methods for ensuring the security of the cloud with special reference to the optimization of the block cipher and stream cipher techniques and the use of hybrid models of encryption. Genetic optimization techniques used will apply genetic algorithm and machine learning cipher to improve on the encryption control and incorporate real-time response to new threats. At the same time, machine learning models are applied to learn with regard to encryption patterns and improve procedures of encryption. Furthermore, simulated annealing is applied for the optimization of the encryption parameters achieving an overall balance between security and performance. Besides, this methodology reinforces data protection against the risks of a single point of failure and guarantees efficient data management in cloud computing, which, in turn, helps to gain more confidence in cloud technologies. For results: https://github.com/niharali/SecureDataExchange.