A Note on the Communication Complexity of Multiparty Computation in the Correlated Randomness Model
A Note on the Communication Complexity of Multiparty Computation in the Correlated Randomness Model
复制标题
关于相关随机模型中多方计算通信复杂度的注解
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Geoffroy Couteau
中科院分区：
文献类型：
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作者：
Geoffroy Couteau
安全多方计算（(mathsf {MPC})）解决了在不损害其隐私的情况下对秘密输入的函数进行评估的挑战。多方计算中的一个核心问题是了解安全评估大小为5的电路所需的通信量。在这项工作中，我们在相关随机模型中的信息理论安全（mathsf {MPC}）设置中重新审视了这个基本问题，其中可信的经销商在协议开始之前将独立于输入的相关随机硬币分发给所有各方。这种设置具有很强的理论意义，并导致了迄今为止已知的最实际有效的（mathsf {MPC}）协议。
Secure multiparty computation ((mathsf {MPC})) addresses the challenge of evaluating functions on secret inputs without compromising their privacy. A central question in multiparty computation is to understand the amount of communication needed to securely evaluate a circuit of size s. In this work, we revisit this fundamental question in the setting of information-theoretically secure (mathsf {MPC}) in the correlated randomness model, where a trusted dealer distributes correlated random coins, independent of the inputs, to all parties before the start of the protocol. This setting is of strong theoretical interest, and has led to the most practically efficient (mathsf {MPC}) protocols known to date.