Privacy-Preserving Updates to Anonymous and Confidential Database

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Provided by: IIR Publications
Topic: Data Management
Format: PDF
The current trend in the application space towards systems of loosely coupled and dynamically bound components that enables just-in-time integration jeopardizes the security of information that is shared between the broker, the requester, and the provider at runtime. In particular, new advances in data mining and knowledge discovery that allow for the extraction of hidden knowledge in an enormous amount of data impose new threats on the seamless integration of information. The authors consider the problem of building privacy preserving algorithms for one category of data mining techniques, association rule mining.
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