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ICDE
2007
IEEE
198views Database» more  ICDE 2007»
14 years 5 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...
SIGMOD
2010
ACM
274views Database» more  SIGMOD 2010»
13 years 9 months ago
K-isomorphism: privacy preserving network publication against structural attacks
Serious concerns on privacy protection in social networks have been raised in recent years; however, research in this area is still in its infancy. The problem is challenging due ...
James Cheng, Ada Wai-Chee Fu, Jia Liu
VLDB
2007
ACM
138views Database» more  VLDB 2007»
13 years 10 months 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...
PVLDB
2008
150views more  PVLDB 2008»
13 years 4 months ago
Privacy preserving serial data publishing by role composition
Previous works about privacy preserving serial data publishing on dynamic databases have relied on unrealistic assumptions of the nature of dynamic databases. In many applications...
Yingyi Bu, Ada Wai-Chee Fu, Raymond Chi-Wing Wong,...
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 4 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...