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A Crypto-Based Approach to Privacy-Preserving Collaborative Data Mining

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2 Author(s)
Zhan, J. ; Heinz Sch., Carnegie Mellon Univ., Pittsburg, PA ; Matwin, S.

To conduct data mining, we often need to collect data from various parties. Privacy concerns may prevent the parties from directly sharing the data and some types of information about the data. How multiple parties collaboratively conduct data mining without breaching data privacy presents a challenge. In this paper, we propose a formal definition of privacy, develop a solution for privacy-preserving k-nearest neighbor classification which is one of data mining tasks, and show that our solution preserves data privacy according to our definition

Published in:

Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on

Date of Conference:

Dec. 2006