Abstract
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.
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Notes
- 1.
Note that there is also a demand node for each donor party in order to ensure that no information about them (e.g., the number of all donor parties) is leaked in our privacy-preserving bartering protocol.
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Acknowledgments
In part, this work was supported by NSF grant #1646999 and DFG grant ME 3704/4-1. This work was carried out while one of the authors was at the National Science Foundation. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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Wüller, S., Breuer, M., Meyer, U., Wetzel, S. (2018). Privacy-Preserving Trade Chain Detection. In: Garcia-Alfaro, J., Herrera-Joancomartí, J., Livraga, G., Rios, R. (eds) Data Privacy Management, Cryptocurrencies and Blockchain Technology. DPM CBT 2018 2018. Lecture Notes in Computer Science(), vol 11025. Springer, Cham. https://doi.org/10.1007/978-3-030-00305-0_26
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DOI: https://doi.org/10.1007/978-3-030-00305-0_26
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