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DAWAK
2006
Springer
15 years 8 months ago
Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures
Abstract. Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view ...
Jiuyong Li, Raymond Chi-Wing Wong, Ada Wai-Chee Fu...
124
Voted
DBSEC
2000
112views Database» more  DBSEC 2000»
15 years 5 months ago
Coordinating Policy for Federated Applications
Abstract At the start of its present term of office in 1997 the UK government published a planning document promising ubiquitous access to Electronic Health Records (EHRs) held wit...
Ken Moody
CCR
2010
133views more  CCR 2010»
15 years 4 months ago
The role of network trace anonymization under attack
In recent years, academic literature has analyzed many attacks on network trace anonymization techniques. These attacks usually correlate external information with anonymized data...
Martin Burkhart, Dominik Schatzmann, Brian Trammel...
CCR
2006
116views more  CCR 2006»
15 years 4 months ago
The devil and packet trace anonymization
Releasing network measurement data--including packet traces-to the research community is a virtuous activity that promotes solid research. However, in practice, releasing anonymiz...
Ruoming Pang, Mark Allman, Vern Paxson, Jason Lee
110
Voted
TKDE
2008
119views more  TKDE 2008»
15 years 4 months ago
Anonymization by Local Recoding in Data with Attribute Hierarchical Taxonomies
Abstract--Individual privacy will be at risk if a published data set is not properly deidentified. k-Anonymity is a major technique to deidentify a data set. Among a number of k-an...
Jiuyong Li, Raymond Chi-Wing Wong, Ada Wai-Chee Fu...