Restricting sensitive query results in information management platforms
Abstract:
As information becomes more accessible to the public, the ability to predict and estimate sensitive data from the data already available to the general public becomes easier. The existing privacy-preserving data mining approaches only consider the information the user is querying and do not consider the information the user already has, and how the user can use that information in combination with the query information to create sensitive data that the user should not have access to. Some embodiments of the present invention provide a query analysis (QA) program that solves the aforementioned problem by taking into account data that a user may already have, whether it is private data or data that is available to the public, and then using that data, along with the data that would be returned in the query, to determine if sensitive data could be recreated.
Information query
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