In this paper, we present a novel multi-party protocol to facilitate the privacy-preserving detection of trade chains in the context of bartering. Our approach is to transform the parties’ private quotes into a flow network such that a minimum-cost flow in this network encodes a set of simultaneously executable trade chains for which the number of parties that can trade is maximized. At the core of our novel protocol is a newly developed privacy-preserving implementation of the cycle canceling algorithm that can be used to solve the minimum cost flow problem on encrypted flow networks.
CITATION STYLE
Wüller, S., Breuer, M., Meyer, U., & Wetzel, S. (2018). Privacy-Preserving Trade Chain Detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11025 LNCS, pp. 373–388). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-00305-0_26
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