Privacy Preserving Clustering Over Distributed Data release_q6ob7lustfes5pg4iomxnr5yc4

Abstract

Privacy prevents sharing of data mainly in data mining applications. Privacy concerns in many application domains for not only prevent sharing of data, but also provide security to the data so that no unauthorised persons can access it. Privacy limits data mining technology to identify patterns and trends from large amount of data. The main aim of privacy preserving clustering is to develop data mining techniques that could be applied on databases without violating the privacy of individuals. In this paperKDPIPELINE algorithm is introduced to preserve privacy over distributed data.
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