Abstract
Design an encryption of privacy preserving and scheduling of intermediate datasets in cloud. Implemenation of encryption is done as follows: Identification of intermediate datasets that needs to be encrypted. Based on frequent pattern mining the least frequent intermediate datasets are encrypted. Perform column level encryption to the sensitive information. Predicting the data based on inference analysis would not be possible. So that the data will be secure when compared to the existing system.
Highlights
To reduce or to save the cost of privacy-preserving of intermediate datasets in cloud, from the original datasets or the public cloud the intermediate datasets are generated through the proper authorization, with that intermediate datasets third party can access modify the data analyse, reanalyse the result and save the modified data .Encrypting ALL datasets is time consuming
System encrypting a part of intermediate datasets while retaining the other datasets based on upper bound privacy leakage constraint approach, Encrypting ALL datasets is time consuming .Size and Frequency of data is static.To identity the leakage Heuristic algorithm is used in Existing system.Figure 1 represent the Block diagram of Existing system
While accessing the table already encrypted data will become the high frequent access table and the table with the high frequent will become least access table .At that time dynamic scheduling is used to monitor the usage of data.Figure 2 represent the Block diagram of proposed system
Summary
To reduce or to save the cost of privacy-preserving of intermediate datasets in cloud, from the original datasets or the public cloud the intermediate datasets are generated through the proper authorization, with that intermediate datasets third party can access modify the data analyse, reanalyse the result and save the modified data .Encrypting ALL datasets is time consuming. The Least frequent intermediate datasets is anonymised and encrypted using homomorphic encryption. All these are analyzed by privacy leakage upper bound based constraint .Encrypting a part of intermediate datasets will save the cost of re-computing and privacy is maintained. When this encryption is not done Inference analysis would be possible the sensitive information can be predicted by comparing multiple intermediate datasets or from the public datasets and it is considered to be static. Encrypting a part of intermediate datasets would save the privacy preserving cost of the data in cloud
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