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» Quantification of a Privacy Preserving Data Mining Transform...
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KDD
2010
ACM
232views Data Mining» more  KDD 2010»
15 years 1 months ago
Discovering frequent patterns in sensitive data
Discovering frequent patterns from data is a popular exploratory technique in data mining. However, if the data are sensitive (e.g. patient health records, user behavior records) ...
Raghav Bhaskar, Srivatsan Laxman, Adam Smith, Abhr...
ICDM
2007
IEEE
104views Data Mining» more  ICDM 2007»
15 years 3 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»
14 years 11 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»
15 years 9 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
ICDM
2006
IEEE
131views Data Mining» more  ICDM 2006»
15 years 3 months ago
Transforming Semi-Honest Protocols to Ensure Accountability
The secure multi-party computation (SMC) model provides means for balancing the use and confidentiality of distributed data. This is especially important in the field of privacy...
Wei Jiang, Chris Clifton