Distribution-preservingk-anonymity
نویسندگان
چکیده
منابع مشابه
Distribution-Preserving k-Anonymity
Preserving the privacy of individuals by protecting their sensitive attributes is an important consideration during microdata release. However, it is equally important to preserve the quality or utility of the data for at least some targeted workloads. We propose a novel framework for privacy preservation based on the k-anonymity model that is ideally suited for workloads that require preservin...
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Microdata is the basis of statistical studies. If microdata is released, it can leak sensitive information about the participants, even if identifiers like name or social security number are removed. A proper anonymization for statistical microdata is essential. K-anonymity has been intensively discussed as a measure for anonymity in statistical data. Quasi identifiers are attributes that might...
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ژورنال
عنوان ژورنال: Statistical Analysis and Data Mining: The ASA Data Science Journal
سال: 2018
ISSN: 1932-1864
DOI: 10.1002/sam.11374