Review of Secure and Optimized Techniques for Data Storage in Cloud Computing

Because of its effectiveness, dependability, and low cost, cloud services are now widely used by a wide range of businesses and individuals. The widespread usage of cloud services has also led to the development of security measures to protect cloud users concerns. Secure cloud computing ensures that the right users may access the data and services. However, protecting cloud-based infrastructures has required a different strategy than the old models, which has led to the emergence of ML-based optimization techniques, despite cryptographic techniques being the primary support in ensuring security. With real-time data processing and threat intelligence, ML may improve the entire security of an IT organization. In this paper the major thrust is on the various secure approaches that have been implemented for the cloud data storage and its security. Apart from it the various ML techniques and its associated optimization approaches that are being utilized in the cloud storage and security have been highlighted. Moreover the comparative analysis of the ML techniques and cryptographic algorithms has been done based on the parameters like accuracy, data security, computational efficiency, time efficiency, throughput etc for inference gathering. It has been inferred that the integration of ML with the cryptographic approaches leads to more efficient techniques for the cloud storage and retrieval.