Protecting data privacy is an important problem in microdata distribution. Anonymization algorithms typically aim to protect individual privacy, with minimal impact on the quality...
Kristen LeFevre, David J. DeWitt, Raghu Ramakrishn...
Limiting disclosure in data publishing requires a careful balance between privacy and utility. Information about individuals must not be revealed, but a dataset should still be us...
Protecting personal data is essential to guarantee the rule of law1 . Due to the new Information and Communication Technologies (ICTs) unprecedented amounts of personal data can b...
According to a famous study [10] of the 1990 census data, 87% of the US population can be uniquely identified by gender, ZIP code and full date of birth. This short paper revisit...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...