Abstract
We consider the problem of securely computing the \(k^{\mathrm {th}}\)-ranked element in a sequence of n private integers distributed among n parties. The \(k^{\mathrm {th}}\)-ranked element (e.g., minimum, maximum, median) is of particular interest in collaborative benchmarking and auctions. Previous secure protocols for the \(k^{\mathrm {th}}\)-ranked element require a communication channel between each pair of parties. A server model naturally fits with the client-server architecture of Internet applications in which clients are connected to the server and not to other clients. It simplifies secure computation by reducing the number of rounds and improves its performance and scalability. In this paper, we propose different approaches for privately computing the \(k^{\mathrm {th}}\)-ranked element in the server model, using either garbled circuits or threshold homomorphic encryption. Our schemes have a constant number of rounds and can compute the \(k^{\mathrm {th}}\)-ranked element within seconds for up to 50 clients in a WAN.
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Acknowledgments
We thank the anonymous reviewers for their valuable comments, and Andreas Fischer and Jonas Böhler for helpful contribution to some implementations.
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Tueno, A., Kerschbaum, F., Katzenbeisser, S., Boev, Y., Qureshi, M. (2020). Secure Computation of the \(k^{\mathrm {th}}\)-Ranked Element in a Star Network. In: Bonneau, J., Heninger, N. (eds) Financial Cryptography and Data Security. FC 2020. Lecture Notes in Computer Science(), vol 12059. Springer, Cham. https://doi.org/10.1007/978-3-030-51280-4_21
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