The exponential growth of collected, processed, and shared microdata has given rise to
concerns about individuals' privacy. As a result, laws and regulations have emerged to …

Most of the existing privacy-preserving techniques, such as k-anonymity methods, are
designed for static data sets. As such, they cannot be applied to streaming data which are …

The exponential growth of collected, processed, and shared microdata has given rise to
concerns about individuals' privacy. As a result, laws and regulations have emerged to …

In this paper, we propose an efficient clustering algorithm that has been applied to the
microaggregation problem. The goal is to partition N given records into clusters, each of …

Microaggregation is a disclosure limitation method that provides security through k-
anonymity by modifying data before release but does not allow suppression of data. We …

We investigate the trade-off between privacy and solution quality that occurs when a k-
anonymized database is used as input to the bin-packing optimization problem. To …

Microaggregation is a statistical disclosure control mechanism to realize k-anonymity as a
basic privacy model. The method first partitions the dataset into groups of at least k records …

Microaggregation is a disclosure control method used to protect microdata. We introduce a
local search method and employ it in an iterated local search algorithm for the NP-hard …

For medical research purposes, having access to large sets of data, often from various
regions, improves statistical outcomes of analysis. However, patient data is usually …

Classical clustering problems search for a partition of objects into a fixed number of clusters.
In many scenarios however the number of clusters is not known or necessarily fixed. Further …