A polynomial-time approximation to optimal multivariate microaggregation

A polynomial-time approximation to optimal multivariate microaggregation

Microaggregation is a family of methods for statistical disclosure control (SDC) of microdata (records on individuals and/or companies), that is, for masking microdata so that they can be released without disclosing private information on the underlying individuals. Microaggregation techniques are currently being used by many statistical agencies. The principle of microaggregation is to group o...

Optimal 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...

A Polynomial Algorithm for Optimal Microaggregation

− Microaggregation is a technique that is used by statistical agencies to limit disclosure of sensitive microdata. Noting that no polynomial time algorithms are known to microaggregate optimally, Domingo-Ferrer and Mateo-Sanz have presented heuristic methods based on hierarchical clustering and genetic algorithms to identify sub-optimal solutions. We present an efficient polynomial time algorit...

A Polynomial Algorithm for Optimal Univariate Microaggregation

Microaggregation is a technique used by statistical agencies to limit disclosure of sensitive microdata. Noting that no polynomial algorithms are known to microaggregate optimally, Domingo-Ferrer and Mateo-Sanz have presented heuristic microaggregation methods. This paper is the first to present an efficient polynomial algorithm for optimal univariate microaggregation. Optimal partitions are sh...

Lectures on multivariate polynomial approximation