A Fast and Efficient Privacy Preserving Data Mining Over Vertically Partitioned Data

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
The goal of data mining is to extract or \"Mine\" knowledge from large amounts of data. However, data is often collected by several different sites. Privacy, legal and commercial concerns restrict centralized access to this data. Theoretical results from the area of secure multiparty computation in cryptography prove that assuming the existence of trapdoor permutations; one may provide secure protocols for any two-party computation as well as for any multiparty computation with honest majority. However, the general methods are far too inefficient and impractical for computing complex functions on inputs consisting of large sets of data.

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