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Effective Privacy Preserving In Leakage Upper Bound Constraints Using Cloud
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In this paper, we propose a upper-bound privacy leakage constraint based approach to identify which intermediate datasets need to be encrypted and which do not, so that privacy preserving cost can be saved while the privacy requirements of data holders can still be satisfied. Cloud computing having a high computation power and storage capacity without any help of the infrastructure to organize the applications to the user. To avoid recomputation intermediate data sets are generated and stored recovering the privacy sensitive information through analyze the multiple intermediate data sets. In such cases, datasets are anonymized rather than encrypted to ensure both data utility and privacy preserving. Privacy preservation of multiple intermediate data sets are create a major problem. But in the existing applications, all the datasets are encrypted and it provides cost effectiveness and efficiency. To verify, which data sets are encrypted and not encrypted. Thus protecting its confidentiality against unintentional errors and attacks.
Keywords
Data Storage Privacy, Encryption and Decryption, Privacy Preserving, Intermediate Dataset, Privacy Upper Bound, Economics of Scale.
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