The collection of large amounts of users’ sensible data by services providers such as Google, Yahoo, or Facebook poses several relevant and challenging issues. A particularly relevant problem is how to ensure a suitable degree of statistical analysis over such data without disrupting user privacy. Toward this end, in the past few years several anonymization and privacy-preserving data mining techniques have been proposed. In this work, we propose a survey of such methodologies and techniques with a particular focus on advanced topics, such as privacy preserving management of time-varying anonymized data and privacy-preserving data mining over distributed data.

Advanced privacy-preserving data management and analysis

Trombetta A.;
2010-01-01

Abstract

The collection of large amounts of users’ sensible data by services providers such as Google, Yahoo, or Facebook poses several relevant and challenging issues. A particularly relevant problem is how to ensure a suitable degree of statistical analysis over such data without disrupting user privacy. Toward this end, in the past few years several anonymization and privacy-preserving data mining techniques have been proposed. In this work, we propose a survey of such methodologies and techniques with a particular focus on advanced topics, such as privacy preserving management of time-varying anonymized data and privacy-preserving data mining over distributed data.
2010
978-1-84996-237-7
978-1-84996-238-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2149995
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