Improving Microaggregation for Complex Record Anonymization
نویسندگان
چکیده
منابع مشابه
Beyond Multivariate Microaggregation for Large Record Anonymization
Microaggregation is one of the most commonly employed microdata protection methods. The basic idea of microaggregation is to anonymize data by aggregating original records into small groups of at least k elements and, therefore, preserving k-anonymity. Usually, in order to avoid information loss, when records are large, i.e., the number of attributes of the data set is large, this data set is s...
متن کاملUtility preserving query log anonymization via semantic microaggregation
Query logs are of great interest for scientists and companies for research, statistical and commercial purposes. However, the availability of query logs for secondary uses raises privacy issues since they allow the identification and/or revelation of sensitive information about individual users. Hence, query anonymization is crucial to avoid identity disclosure. To enable the publication of pri...
متن کاملImproving the Utility of Differential Privacy via Univariate Microaggregation
Differential privacy is a privacy model for anonymization that offers more robust privacy guarantees than previous models, such as k-anonymity and its extensions. However, it is often disregarded that the utility of differentially private outputs is quite limited, either because of the amount of noise that needs to be added to obtain them or because utility is only preserved for a restricted ty...
متن کاملOptimal Multivariate 2-Microaggregation for Microdata Protection: A 2-Approximation
Microaggregation is a special clustering problem where the goal is to cluster a set of points into groups of at least k points in such a way that groups are as homogeneous as possible. Microaggregation arises in connection with anonymization of statistical databases for privacy protection (k-anonymity), where points are assimilated to database records. A usual group homogeneity criterion is wit...
متن کاملDisclosure Control by Computer Scientists: An Overview and an Application of Microaggregation to Mobility Data Anonymization
Privacy-preserving data mining (PPDM) is a subdiscipline of computer science which in many respects is parallel to statistical disclosure control (SDC) within statistics. See [12] for a survey of recent developments in PPDM. We focus here on the connections between k-anonymity, a concept arisen in the PPDM community, and microaggregation, a family of methods developed within SDC. This is discus...
متن کامل