Welcome to the resource topic for 2008/197
Title:
Secure Multiparty Computation for Privacy-Preserving Data Mining
Authors: Yehuda Lindell, 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.
ePrint: https://eprint.iacr.org/2008/197
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