Mining health data can lead to faster medical decisions, improvement in the quality of
treatment, disease prevention, and reduced cost, and it drives innovative solutions within the …

The internet is increasingly becoming a standard for both the production and consumption of
data while at the same time cyber-crime involving the theft of private data is growing …

Abstract k-Anonymity is a useful concept to solve the tension between data utility and
respondent privacy in individual data (microdata) protection. However, the generalization …

This paper presents a clustering algorithm for partitioning a minimum spanning tree with a
constraint on minimum group size. The problem is motivated by microaggregation, a …

This paper explores the challenges raised by big data in privacy-preserving data
management. First, we examine the conflicts raised by big data with respect to preexisting …

Microaggregation is a technique for disclosure limitation aimed at protecting the privacy of
data subjects in microdata releases. It has been used as an alternative to generalization and …

Today's globally networked society places great demand on the dissemination and sharing
of information, which is probably becoming the most important and demanded resource …

The current social and economic context increasingly demands open data to improve
scientific research and decision making. However, when published data refer to individual …

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 …

Microaggregation is a technique used by statistical agencies to limit disclosure of sensitive
microdata. Noting that no polynomial algorithms are known to microaggregate optimally …