The extensive collection and processing of personal information in big data analytics has
given rise to serious privacy concerns, related to wide scale electronic surveillance, profiling …

Data privacy studies methods, tools, and theory to avoid the disclosure of sensitive
information. Its origin is in statistics with the goal to ensure the confidentiality of data …

Data privacy is now a hot topic. Big data have increased its importance. Nevertheless,
computational methods for data privacy have been studied and developed since the 70s, at …

35 Privacy in Data Mining Page 1 35 Privacy in Data Mining Vicenç Torra IIIA - CSIC, Campus
UAB s/n, 08193 Bellaterra Catalonia, Spain vtorra@iiia.csic.es Summary. In this chapter we …

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 …

In this paper, we define I-fuzzy partitions (or intuitionistic fuzzy partitions as called by
Atanassov or interval-valued fuzzy partitions). As our ultimate goal is to compare the results …

Motivated by our research on specific information loss measures (in privacy preserving data
mining) and our need to compare fuzzy clusters, we proposed in a recent paper a definition …

Microaggregation is known as a successful perturbative mechanism to realize k-anonymity.
The method partitions the dataset into groups of at least k members and then aggregates the …

In a recent paper we introduced intuitionistic fuzzy partitions or interval-valued fuzzy
partitions as a way to represent the uncertainty of fuzzy clustering. In this paper we …

In this chapter we review some of our results related to the use of clustering in the area of
data privacy. The paper gives a brief overview of data privacy and, more specifically, on data …