|Title||Privacy-preserving Collaborative Data Mining|
|Publication Type||Conference Proceedings|
|Year of Publication||2003|
|Conference Name||ICDM Foundation and New Directions of Data Mining workshop|
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. We present a secure framework for multiple parties to conduct privacy-preserving association rule mining.