We present a new circuit-based protocol for multi-party private set intersection (PSI) that allows m parties to compute the intersection of their datasets without revealing any additional information about the items outside the intersection. Building upon the two-party Sort-Compare-Shuffle (SCS) protocol, we seamlessly extend it to a multi-party setting. Demonstrating its practicality through implementation, our protocol exhibits acceptable performance. Specifically, with 7 parties, each possessing a set size of 2^{12}, our protocol completes in just 19 seconds. Moreover, circuit-based protocols like ours have an advantage over using custom protocols to perform more complex computation. We substantiate this advantage by incorporating a module for calculating the Jaccard similarity metric of the private sets which can be used in the application domain of network traffic analysis for anomaly detection. This extension showcases the versatility of our protocol beyond set intersection computations, demonstrating its efficacy in preserving privacy while efficiently identifying abnormal patterns in network flow.

翻译：我们提出了一种新的基于电路的多方隐私集合交集（PSI）协议，该协议允许m方在不泄露交集之外任何元素信息的前提下计算各自数据集的交集。基于两方排序-比较-洗牌（SCS）协议，我们将其无缝扩展至多方场景。通过实现验证，我们的协议展现出可接受的性能：在7方各自拥有2^12规模集合的条件下，协议仅需19秒即可完成。此外，与定制协议相比，基于电路的协议（如本方案）在支持更复杂计算方面具有优势。通过引入计算私有集合杰卡德相似度指标的模块，我们进一步验证了这一优势——该指标可应用于网络流量分析的异常检测场景。该扩展不仅展示了协议在集合交集计算之外的通用性，更证实了其在高效识别网络流异常模式的同时保护隐私的有效性。