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» State-of-the-art in privacy preserving data mining
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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 8 months ago
Transforming data to satisfy privacy constraints
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...
Vijay S. Iyengar
TLCA
2005
Springer
14 years 29 days ago
Privacy in Data Mining Using Formal Methods
There is growing public concern about personal data collected by both private and public sectors. People have very little control over what kinds of data are stored and how such da...
Stan Matwin, Amy P. Felty, István T. Hern&a...
KDD
2010
ACM
232views Data Mining» more  KDD 2010»
13 years 11 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...
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
KDD
2008
ACM
162views Data Mining» more  KDD 2008»
14 years 8 months ago
Composition attacks and auxiliary information in data privacy
Privacy is an increasingly important aspect of data publishing. Reasoning about privacy, however, is fraught with pitfalls. One of the most significant is the auxiliary informatio...
Srivatsava Ranjit Ganta, Shiva Prasad Kasiviswanat...