CRNIApr 7, 2021

Shared-Dining: Broadcasting Secret Shares using Dining-Cryptographers Groups

arXiv:2104.03032v12 citations
AI Analysis

This work addresses privacy and incentive issues in anonymous communication systems, particularly for high-stakes domains like finance, though it appears incremental as it builds on existing dining-cryptographers and secret-sharing methods.

The paper tackles the problem of ensuring anonymity in k-anonymous broadcast by addressing incentives for group members to forward messages, using a modified dining-cryptographers protocol to distribute Shamir's secret shares, which prevents privacy breaches if fewer than k shares are broadcast. It achieves (n-|attackers|)-anonymity for up to k-1 attackers with throughput rates of 10-100 kB/s suitable for applications like financial blockchain systems.

A k-anonymous broadcast can be implemented using a small group of dining cryptographers to first share the message, followed by a flooding phase started by group members. Members have little incentive to forward the message in a timely manner, as forwarding incurs costs, or they may even profit from keeping the message. In worst case, this leaves the true originator as the only sender, rendering the dining-cryptographers phase useless and compromising their privacy. We present a novel approach using a modified dining-cryptographers protocol to distributed shares of an (n,k)-Shamir's secret sharing scheme. Finally, all group members broadcast their received share through the network, allowing any recipient of k shares to reconstruct the message, enforcing anonymity. If less than k group members broadcast their shares, the message cannot be decoded thus preventing privacy breaches for the originator. Our system provides (n-|attackers|)-anonymity for up to k-1 attackers and has little performance impact on dissemination. We show these results in a security analysis and performance evaluation based on a proof-of-concept prototype. Throughput rates between 10 and 100 kB/s are enough for many real applications with high privacy requirements, e.g., financial blockchain system.

Foundations

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