Secure Private Data Release In Vertical Partitioned Data
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2014, Vol 2, Issue 11
Abstract
When mining the useful information some privacy preserving data publishing addresses the problem of exposing the sensitive data. In this paper, the source database table is divided into some parties which hold different attributes for the same set of individuals where we address the problem of private data publishing. For this we extend the differential privacy model and proposed the algorithm for vertically partitioned data which guarantees that the other party can’t derive extra information from the answered query. This method will provide the security for the private data which is released from the scattered framework.
Authors and Affiliations
Kanchan Kauthale, Lakshmi Madhuri
Keywords
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- EP ID EP19049
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