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» Optimal randomization for privacy preserving data mining
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KDD
2004
ACM
159views Data Mining» more  KDD 2004»
13 years 9 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
ICDE
2008
IEEE
157views Database» more  ICDE 2008»
14 years 5 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
PODS
2003
ACM
156views Database» more  PODS 2003»
14 years 4 months ago
Limiting privacy breaches in privacy preserving data mining
There has been increasing interest in the problem of building accurate data mining models over aggregate data, while protecting privacy at the level of individual records. One app...
Alexandre V. Evfimievski, Johannes Gehrke, Ramakri...
SIGKDD
2002
93views more  SIGKDD 2002»
13 years 4 months ago
Randomization in Privacy-Preserving Data Mining
Suppose there are many clients, each having some personal information, and one server, which is interested only in aggregate, statistically significant, properties of this informa...
Alexandre V. Evfimievski
ICEB
2004
175views Business» more  ICEB 2004»
13 years 5 months ago
Privacy-Preserving Data Mining in Electronic Surveys
Electronic surveys are an important resource in data mining. However, how to protect respondents' data privacy during the survey is a challenge to the security and privacy co...
Justin Z. Zhan, Stan Matwin