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A Secure Multiparty Product Protocol for Preserving the Privacy in Collaborative Data Mining
Author(s) -
G.Chitra Ganapathi,
G. Swathi,
S. Karthick
Publication year - 2010
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/264-423
Subject(s) - computer science , protocol (science) , product (mathematics) , computer security , internet privacy , medicine , alternative medicine , pathology , geometry , mathematics
In the modern business world, collaborative data mining becomes especially important because of the mutual benefit it brings to the collaborators. During the collaboration, each party of the collaboration needs to share its data with other parties. If the parties don't care about their data privacy, the collaboration can be easily achieved. Privacy concerns parties, each having a private data set, want to jointly conduct association rule mining without disclosing their private data to other parties. This paper deals with how to conduct collaborative data mining, one of the core data mining techniques, on private data. There is no central, trusted party having access to all the data. Instead, a protocol using Homomorphic encryption-techniques, to exchange the data while keeping it private, is used. The full text of the article is not available in the cache. Kindly refer the IJCA digital library at www.ijcaonline.org for the complete article. In case, you face problems while downloading the full-text, please send a mail to editor at editor@ijcaonline.org

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