Security and High Performance Data Classification for Cloud Storage

Abstract

Cloud storage is crucial for modern data management, but security remains a challenge due to the increasing number of cyber threats and data breaches. By dividing information into three different classes—public, sensitive, and confidential—this article suggests a strong security mechanism for cloud storage. Public data undergoes basic integrity checks, sensitive data undergoes moderate encryption, and secret material undergoes strong encryption and stringent integrity controls. These individualized approaches are based on the method's assessment of the sensitivity of the various data classes. For better data security in cloud storage, this research suggests a novel design for format-preserving encryption based on random Sboxes substitution-permutation networks. This research introduces a novel categorization approach that classify data into appropriate encryption systems based on their class, thereby merging the fields of machine learning and multi-criteria decision-making. According to the simulation findings, our solution guarantees data security and integrity while being more efficient, accurate, and requiring less processing time.