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» On privacy preservation against adversarial data mining
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PVLDB
2008
146views more  PVLDB 2008»
13 years 7 months ago
Resisting structural re-identification in anonymized social networks
We identify privacy risks associated with releasing network data sets and provide an algorithm that mitigates those risks. A network consists of entities connected by links repres...
Michael Hay, Gerome Miklau, David Jensen, Donald F...
ICDM
2007
IEEE
104views Data Mining» more  ICDM 2007»
14 years 2 months ago
Secure Logistic Regression of Horizontally and Vertically Partitioned Distributed Databases
Privacy-preserving data mining (PPDM) techniques aim to construct efficient data mining algorithms while maintaining privacy. Statistical disclosure limitation (SDL) techniques a...
Aleksandra B. Slavkovic, Yuval Nardi, Matthew M. T...
CASCON
2004
129views Education» more  CASCON 2004»
13 years 9 months ago
Building predictors from vertically distributed data
Due in part to the large volume of data available today, but more importantly to privacy concerns, data are often distributed across institutional, geographical and organizational...
Sabine M. McConnell, David B. Skillicorn
SIGMOD
2005
ACM
128views Database» more  SIGMOD 2005»
14 years 7 months ago
Deriving Private Information from Randomized Data
Randomization has emerged as a useful technique for data disguising in privacy-preserving data mining. Its privacy properties have been studied in a number of papers. Kargupta et ...
Zhengli Huang, Wenliang Du, Biao Chen
KDD
2008
ACM
134views Data Mining» more  KDD 2008»
14 years 8 months ago
Privacy-preserving cox regression for survival analysis
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...
Shipeng Yu, Glenn Fung, Rómer Rosales, Srir...