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KDD
2006
ACM
128views Data Mining» more  KDD 2006»
16 years 7 days ago
Workload-aware anonymization
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...
SIGMOD
2006
ACM
96views Database» more  SIGMOD 2006»
15 years 12 months ago
Injecting utility into anonymized datasets
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...
Daniel Kifer, Johannes Gehrke
IEEEARES
2008
IEEE
15 years 6 months ago
A Post-processing Method to Lessen k-Anonymity Dissimilarities
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...
Agusti Solanas, Gloria Pujol, Antoni Martín...
WPES
2006
ACM
15 years 5 months ago
Revisiting the uniqueness of simple demographics in the US population
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...
Philippe Golle
ICDM
2003
IEEE
112views Data Mining» more  ICDM 2003»
15 years 5 months ago
Privacy-preserving Distributed Clustering using Generative Models
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
Srujana Merugu, Joydeep Ghosh