Abstract Secure Multi-party Computation (SMPC) is a family of protocols which allow some
parties to compute a function on their private inputs, obtaining the output at the end and …

In the era of big data with an ever-increasing amount of data, the demand for data
processing is increasing, and various computing service agreements have also been …

Private set intersection protocols allow two parties with private sets of data to compute the
intersection between them without leaking other information about their sets. These …

With the rapid development of edge computing and the Internet of Things, the problem of
information resource sharing can be effectively solved through multi-party collaboration, but …

With the rapid development of new technologies, such as the Internet and big data, more
and more distributed data need to be processed by multiple parties. Therefore, privacy …

Multiparty Private Set Intersection (MPSI) is dedicated to finding the intersection of datasets
of multiple participants without disclosing any other information. Although many MPSI …

随着互联网, 大数据等新技术的快速发展, 越来越多的分布式数据需要多方协作处理,
隐私保护技术由此面临更大的挑战. 安全多方计算是一种重要的隐私保护技术 …

Sample alignment technique is a key component of vertical federated learning. One of the
important solutions for sample alignment is known as private set intersection (PSI). It …

In big data analytics, Jaccard similarity is a widely used block for scalable similarity
computation. It is broadly applied in the Internet of Things (IoT) applications, such as credit …

超阈值多方隐私集合求交协议 (OT-MP-PSI) 是 PSI 协议的变体, 允许 m 个参与方共同计算至少 t
(t≤ m) 个参与方中拥有相同元素的超阈值交集, 且保证仅拥有超阈值元素的参与方才能知晓该 …