For the privacy-preserving computation of multi-source large scale data sets, the secure multi-party computation protocol with high-throughput is of the utmost importance. However, the existing high-throughput secure multi-party protocols only involve the fixed 3-party or 4-party setting, limiting its practicality. To achieve a high-throughput n-party (n ≥ 3) secure protocol, low communication and simple computation are two major issues to be considered, which can be used to reduce network load and increase concurrency processing. In this paper, we design a secure multi-party multiplication protocol with only a single round interaction and simple computation by using replicated sharing, which is generated according to the partition of all cross-terms in the sharing-based multiplication operation. Furthermore, in order to implement the optimal communication for each round, we model all cross-terms of the sharing-based multiplication operation as a bipartite graph, and propose a bipartite graph partitioning algorithm. Due to the bipartite graph model, the optimal partition of the cross-terms can be reduced to partition the bipartite graph into n independent subgraphs with the least number of vertices in each subgraph. Finally, the evaluation results show the proposed protocol is both low communication and simple computation. In the case of the 4-party setting Boolean circuits, it only needs to send 1.5 bits and carry out 4 AND and 3 XOR operations on average per AND gate for each party, and achieving a rate of over 0.65 million AES per second.

对于多源大规模数据集的隐私保护计算，具有高吞吐量的安全的多方计算协议至关重要。但是，现有的高吞吐量安全多方协议仅涉及固定的3方或4方设置，从而限制了其实用性。为了实现高通量ñ三方（ñ≥3）安全协议，低通信量和简单计算是需要考虑的两个主要问题，可用于减少网络负载和增加并发处理。在本文中，我们设计了一种安全的多方乘法协议，该协议只有一次交互操作，并且通过使用基于共享的乘法运算中所有交叉项的分区生成的复制共享，可以轻松地进行计算。此外，为了实现每一轮的最佳通信，我们将基于共享的乘法运算的所有交叉项建模为二部图，并提出了二部图分区算法。由于使用了二部图模型，可以减少交叉项的最佳划分，从而将二部图划分为n个每个子图中具有最少顶点数的独立子图。最后，评估结果表明所提出的协议通信量低，计算简单。在四方设置布尔电路的情况下，每个方的每个“与”门平均仅需要发送1.5位并执行4个“与”和3个“异或”运算，并且每秒可实现超过65万个AES。