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» On the Design and Quantification of Privacy Preserving Data ...
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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 7 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 16 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...
SDM
2007
SIAM
130views Data Mining» more  SDM 2007»
13 years 8 months ago
Towards Attack-Resilient Geometric Data Perturbation
Data perturbation is a popular technique for privacypreserving data mining. The major challenge of data perturbation is balancing privacy protection and data quality, which are no...
Keke Chen, Gordon Sun, Ling Liu
CIKM
2009
Springer
14 years 1 months ago
Walking in the crowd: anonymizing trajectory data for pattern analysis
Recently, trajectory data mining has received a lot of attention in both the industry and the academic research. In this paper, we study the privacy threats in trajectory data pub...
Noman Mohammed, Benjamin C. M. Fung, Mourad Debbab...
ADC
2007
Springer
145views Database» more  ADC 2007»
14 years 1 months ago
The Privacy of k-NN Retrieval for Horizontal Partitioned Data -- New Methods and Applications
Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...
Artak Amirbekyan, Vladimir Estivill-Castro