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» Privacy-Preserving Data Mining
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SAC
2006
ACM
14 years 3 months ago
On the use of spectral filtering for privacy preserving data mining
Randomization has been a primary tool to hide sensitive private information during privacy preserving data mining.The previous work based on spectral filtering, show the noise ma...
Songtao Guo, Xintao Wu
KDD
2004
ACM
159views Data Mining» more  KDD 2004»
14 years 3 months ago
Optimal randomization for privacy preserving data mining
Randomization is an economical and efficient approach for privacy preserving data mining (PPDM). In order to guarantee the performance of data mining and the protection of individ...
Michael Yu Zhu, Lei Liu
ICDM
2005
IEEE
153views Data Mining» more  ICDM 2005»
14 years 3 months ago
Privacy-Preserving Frequent Pattern Mining across Private Databases
Privacy consideration has much significance in the application of data mining. It is very important that the privacy of individual parties will not be exposed when data mining te...
Ada Wai-Chee Fu, Raymond Chi-Wing Wong, Ke Wang
PODS
2001
ACM
148views Database» more  PODS 2001»
14 years 10 months ago
On the Design and Quantification of Privacy Preserving Data Mining Algorithms
The increasing ability to track and collect large amounts of data with the use of current hardware technology has lead to an interest in the development of data mining algorithms ...
Dakshi Agrawal, Charu C. Aggarwal
ICDE
2008
IEEE
157views Database» more  ICDE 2008»
14 years 11 months ago
OptRR: Optimizing Randomized Response Schemes for Privacy-Preserving Data Mining
The randomized response (RR) technique is a promising technique to disguise private categorical data in Privacy-Preserving Data Mining (PPDM). Although a number of RR-based methods...
Zhengli Huang, Wenliang Du