In numerous data application scenarios, various data can be represented in the form of data sets, and the intersection is often the common concern of multiple users. Using private set intersection (PSI) protocol, users can securely compute the intersection of their sets without disclosing their private input and other additional information. At the same time, there is also a strong practical demand for statistical analysis of intersection data. However, when multiple parties are involved, the efficiency of the multiparty PSI protocol decreases dramatically as the number of users increases. In this paper, we construct a novel server-aided multiparty PSI protocol, which can transform the complex multiparty computation problem into an efficient two-party computation problem. In addition, we design a series of server-aided party PSI statistical protocols to compute the statistics of the intersection elements, such as the sum, average, variance, range (maximum, minimum), and the cardinality of intersection (the size of intersection). In our protocol, the clients only need to upload their private data to the servers in blinded form and do not need to keep online during server computing. Experiments show that our protocol has high computation and communication efficiency and is suitable for lightweight clients. In addition, we also introduce an application of our protocols in the field of intelligent logistics.

中文翻译：

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面向轻量级客户端的服务器辅助多方私有集交集协议及其在智能物流中的应用

在众多的数据应用场景中，各种数据都可以用数据集的形式表示，交集往往是多个用户共同关心的问题。使用私有集交集 (PSI) 协议，用户可以安全地计算他们的集的交集，而无需泄露他们的私有输入和其他附加信息。同时，对路口数据的统计分析也有很强的实际需求。然而，当涉及多方时，多方PSI协议的效率会随着用户数量的增加而急剧下降。在本文中，我们构建了一种新颖的服务器辅助多方 PSI 协议，可以将复杂的多方计算问题转化为高效的两方计算问题。此外，我们设计了一系列服务器辅助方PSI统计协议来计算交集元素的统计量，如总和、平均值、方差、范围（最大、最小）和交集的基数（交集的大小）。在我们的协议中，客户端只需要将他们的隐私数据以盲的形式上传到服务器，而无需在服务器计算期间保持在线。实验表明，我们的协议具有较高的计算和通信效率，适用于轻量级客户端。此外，我们还介绍了我们的协议在智能物流领域的一个应用。客户端只需要将自己的隐私数据以不公开的方式上传到服务器，服务器计算过程中不需要一直在线。实验表明，我们的协议具有较高的计算和通信效率，适用于轻量级客户端。此外，我们还介绍了我们的协议在智能物流领域的一个应用。客户端只需要将自己的隐私数据以不公开的方式上传到服务器，服务器计算过程中不需要一直在线。实验表明，我们的协议具有较高的计算和通信效率，适用于轻量级客户端。此外，我们还介绍了我们的协议在智能物流领域的一个应用。