Improved Association Rule Mining-Based Data Sanitization for Privacy Preservation Model in Cloud

Data security in cloud services is achieved by imposing a broad range of privacy settings and restrictions. However, the different techniques used fail to eliminate hazard serious data leakage, information loss other vulnerabilities. Therefore, better policy requirements are necessary ensure acceptable protection levels cloud. The two procedures presented this paper intended build new method. Here, sensitive stored big datasets protected from abuse via sanitization procedure relying on an improved apriori approach clean data. main objective case generate key using optimization technique known as Corona-integrated Archimedes Optimization with Tent Map Estimation (CIAO-TME). Such deals both restoration problem optimizing preservation ratio (IPR), hiding (HR), degree modification (DOM) formulated researched well.