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ICDE
2007
IEEE
198views Database» more  ICDE 2007»
14 years 7 months ago
Worst-Case Background Knowledge for Privacy-Preserving Data Publishing
Recent work has shown the necessity of considering an attacker's background knowledge when reasoning about privacy in data publishing. However, in practice, the data publishe...
David J. Martin, Daniel Kifer, Ashwin Machanavajjh...
VLDB
2007
ACM
138views Database» more  VLDB 2007»
14 years 13 days ago
Minimality Attack in Privacy Preserving Data Publishing
Data publishing generates much concern over the protection of individual privacy. In the well-known kanonymity model and the related models such as l-diversity and (α, k)-anonymi...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, J...
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 6 months ago
Privacy-Preserving Data Mining through Knowledge Model Sharing
Privacy-preserving data mining (PPDM) is an important topic to both industry and academia. In general there are two approaches to tackling PPDM, one is statistics-based and the oth...
Patrick Sharkey, Hongwei Tian, Weining Zhang, Shou...
ICDE
2009
IEEE
141views Database» more  ICDE 2009»
14 years 8 months ago
Privacy Preserving Publishing on Multiple Quasi-identifiers
In some applications of privacy preserving data publishing, a practical demand is to publish a data set on multiple quasi-identifiers for multiple users simultaneously, which poses...
Jian Pei, Yufei Tao, Jiexing Li, Xiaokui Xiao
ISI
2008
Springer
13 years 5 months ago
A framework for privacy-preserving cluster analysis
Abstract--Releasing person-specific data could potentially reveal sensitive information of individuals. k-anonymization is a promising privacy protection mechanism in data publishi...
Benjamin C. M. Fung, Ke Wang, Lingyu Wang, Mourad ...