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Filtering for Private Collaborative Benchmarking

  • Conference paper
Emerging Trends in Information and Communication Security (ETRICS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 3995))

Abstract

Collaborative Benchmarking is an important issue for modern enterprises, but the business performance quantities used as input are often highly confidential. Secure Multi-Party Computation can offer protocols that can compute benchmarks without leaking the input variables. Benchmarking is a process of comparing to the “best”, so often it is necessary to only include the k-best enterprises for computing a benchmark to not distort the result with some outlying performances. We present a protocol that can be used as a filter, before running any collaborative benchmarking protocol that restricts the participants to the k best values. Our protocol doesn’t use the general circuit construction technique for SMC aiming to optimize performance. As building blocks we present the fastest implementation of Yao’s millionaires’ protocol and a protocol that achieves a fair shuffle in O(log n) rounds.

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Author information

Authors and Affiliations

  1. SAP Research, Karlsruhe, Germany

    Florian Kerschbaum & Orestis Terzidis

Authors
  1. Florian Kerschbaum
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  2. Orestis Terzidis
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Editor information

Editors and Affiliations

  1. Institut für Informatik und Gesellschaft, Abt. Telematik, Albert-Ludwigs-Universität Freiburg, Friedrichstr. 50, 79098, Freiburg, Germany

    Günter Müller

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Kerschbaum, F., Terzidis, O. (2006). Filtering for Private Collaborative Benchmarking. In: Müller, G. (eds) Emerging Trends in Information and Communication Security. ETRICS 2006. Lecture Notes in Computer Science, vol 3995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11766155_29

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  • DOI: https://doi.org/10.1007/11766155_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34640-1

  • Online ISBN: 978-3-540-34642-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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