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ISI
2007
Springer

Privacy Preserving Collaborative Data Mining

8 years 6 months ago
Privacy Preserving Collaborative Data Mining
Privacy-preserving data mining is an important issue in the areas of data mining and security. In this paper, we study how to conduct association rule mining, one of the core data mining techniques, on private data in the following scenario: Multiple parties, each having a private data set, want to jointly conduct association rule mining without disclosing their private data to other parties. Because of the interactive nature among parties, developing a secure framework to achieve such a computation is both challenging and desirable. In this paper, we present a secure framework for multiple parties to conduct privacy-preserving association rule mining. Key Words: privacy, security, association rule mining, secure multi-party computation.
Justin Z. Zhan
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2007
Where ISI
Authors Justin Z. Zhan
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