DocumentCode
3260700
Title
A Crypto-Based Approach to Privacy-Preserving Collaborative Data Mining
Author
Zhan, Justin ; Matwin, Stan
Author_Institution
Heinz Sch., Carnegie Mellon Univ., Pittsburg, PA
fYear
2006
fDate
Dec. 2006
Firstpage
546
Lastpage
550
Abstract
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
Keywords
cryptography; data mining; data privacy; pattern classification; collaborative data mining; crypto based approach; k-nearest neighbor classification; privacy preservation; Collaboration; Cryptography; Data mining; Data privacy; Data security; Delta modulation; Information security; Information technology; Protection; Protocols;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
0-7695-2702-7
Type
conf
DOI
10.1109/ICDMW.2006.3
Filename
4063687
Link To Document