Semantic Adaptive Microaggregation of Categorical Microdata

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Provided by: Universitat Rostock
Topic: Security
Format: PDF
In the context of statistical disclosure control, microaggregation is a privacy preserving method aimed to mask sensitive microdata prior to publication. It iteratively creates clusters of, at least, k elements, and replaces them by their prototype so that they become k-indistinguishable (anonymous). This data transformation produces a loss of information with regards to the original dataset which affects the utility of masked data, so, the aim of microaggregation algorithms is to find the partition that minimizes the information loss while ensuring a certain level of privacy.
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