Improving the Implementation of New Approach for Data Privacy Preserving in Data Mining Using Slicing

Provided by: International Journal of Modern Engineering Research (IJMER)
Topic: Data Management
Format: PDF
Some different anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving micro data publishing. Recent work has shown that generalization loses considerable amount of information, especially for high dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. In this paper, the authors present a novel technique called slicing, which partitions the data both horizontally and vertically.

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