The More the Merrier: Reducing the Cost of Large Scale MPC
The More the Merrier: Reducing the Cost of Large Scale MPC
复制标题
越多越好：降低大规模 MPC 的成本
DOI：
10.1007/978-3-030-77886-6_24
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Yerukhimovich, Arkady
中科院分区：
文献类型：
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作者：
Gordon, S. Dov;Starin, Daniel;Yerukhimovich, Arkady
安全多方计算（MPC）允许多方在其私有输入上执行安全联合计算。如今，MPC的应用程序正在增长，成千上万的各方希望为区块链构建联合机器学习模型或可信设置。为了解决这种情况下，我们提出了一套新颖的MPC协议，最大限度地提高吞吐量时，大量的缔约方。特别是，我们的协议都有通信和计算的复杂性，减少与缔约方的数量。我们的协议建立在先前的协议的基础上打包秘密共享，引入新的技术，以建立更有效的计算一般电路。具体来说，我们引入了一种新的方法来处理线性攻击中出现的协议使用打包秘密共享，我们提出了一种方法，用于解包共享乘法三元组，而不增加渐近成本。与以前的工作相比，我们避免了一般编译电路大小时所需的开销|C|的SIMD计算中使用，我们改进了民间传说的“基于委员会”的解决方案的一个因素O（s），统计安全参数。在实践中，我们的协议是高达10倍的速度比任何已知的建设，在一组合理的参数。
Secure multi-party computation (MPC) allows multiple parties to perform secure joint computations on their private inputs. Today, applications for MPC are growing with thousands of parties wishing to build federated machine learning models or trusted setups for blockchains. To address such scenarios we propose a suite of novel MPC protocols that maximize throughput when run with large numbers of parties. In particular, our protocols have both communication and computation complexity that decrease with the number of parties. Our protocols buildon prior protocolsbased on packed secret-sharing, introducing new techniques to build more efficient computation for general circuits. Specifically, we introduce a new approach for handlinglinear attacksthat arise in protocols using packed secret-sharing and we propose a method for unpacking shared multiplication triples without increasing the asymptotic costs. Compared with prior work, we avoid theoverhead required when generically compiling circuits of size |C| for use in a SIMD computation, and we improve over folklore “committee-based” solutions by a factor ofO(s), the statistical security parameter. In practice, our protocol is up to 10Xfaster than any known construction, under a reasonable set of parameters.