PRIVACY PRESERVING FOR DATA PUBLISHING WITH SEARCH AND COMPUTE ON ENCRYPTED DATA

Computer Science And Engineering

Privacy preserving for data publishing that indicates large number of data is formed due to number of providers are more when the data to be published and time elapsed for data searching. This task is non trivial, because the utility measuring usually requires the aggregated raw data, which is not revealed to the data users due to private concerns. Furthermore, the data publishers may even cheat in the raw data, since no one including the individual providers, knows the full data set. The relevant encrypted data sets in sequence. We are interested in efficiently processing queries that require both operations to be performed on fully encrypted databases.One immediate solution is to use several special-purpose encryption schemes simultaneously; however, this approach is associated with a high computational cost for maintaining multiple encryption contexts. Another solution is to use a privacy scheme. However, no secure solutions have been developed that satisfy the efficiency requirements. We constructs a unified framework to efficiently and privately process queries. In this paper, we propose secure data publishing without having any duplication and privately process queries with search and compute operations on a database.

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