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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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
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