Preserving Privacy in Data Mining using Data Distortion Approach

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Provided by: University of Muenster
Topic: Big Data
Format: PDF
Data mining, the extraction of hidden predictive information from large databases, is nothing but discovering hidden value in the data warehouse. Because of the increasing ability to trace and collect large amount of personal information, privacy preserving in data mining applications has become an important concern. Data distortion is one of the well known techniques for privacy preserving data mining. The objective of these data perturbation techniques is to distort the individual data values while preserving the underlying statistical distribution properties.
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