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Encyclopedia of Database Systems pp 1–7Cite as

Secure Multiparty Computation Methods

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Definition

The problem of preserving privacy while allowing data analysis can be attacked in many ways. One way is to avoid disclosing data beyond its source while still constructing data mining models equivalent to those that would have been learned on an integrated data set. This follows the approach of Secure Multiparty Computation (SMC). SMC refers to the general problem of computing a given function securely over private inputs while revealing nothing extra to any party except what can be inferred (in polynomial time) from its input and output. Since one can prove that data are not disclosed beyond its original source, the opportunity for misuse is not increased by the process of data mining.

The definition of privacy followed in this line of research is conceptually simple: no site should learn anything new from the processof data mining. Specifically, anything learned during the data mining process must be derivable given one’s own data and the final result. In other words,...

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Author information

Authors and Affiliations

  1. University of Texas at Dallas, Richardson, TX, USA

    Murat Kantarcolu

  2. Rutgers University, Newark, NJ, USA

    Jaideep Vaidya

Authors
  1. Murat Kantarcolu
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  2. Jaideep Vaidya
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Corresponding author

Correspondence to Murat Kantarcolu .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Department of Computer Science, Purdue University, 305 N University St., 47907-2107, West Lafayette, IN, USA

    Chris Clifton

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Kantarcolu, M., Vaidya, J. (2017). Secure Multiparty Computation Methods. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_1388-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_1388-2

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4899-7993-3

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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