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Paper 2008/197

Secure Multiparty Computation for Privacy-Preserving Data Mining

Yehuda Lindell and Benny Pinkas

Abstract

In this paper, we survey the basic paradigms and notions of secure multiparty computation and discuss their relevance to the field of privacy-preserving data mining. In addition to reviewing definitions and constructions for secure multiparty computation, we discuss the issue of efficiency and demonstrate the difficulties involved in constructing highly efficient protocols. We also present common errors that are prevalent in the literature when secure multiparty computation techniques are applied to privacy-preserving data mining. Finally, we discuss the relationship between secure multiparty computation and privacy-preserving data mining, and show which problems it solves and which problems it does not.

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Published elsewhere. Unknown where it was published
Keywords
Secure Multiparty ComputationPrivacy-Preserving Data Mininf
Contact author(s)
benny @ pinkas net
History
2008-05-12: received
Short URL
https://ia.cr/2008/197
License
Creative Commons Attribution
CC BY
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