We introduce Private Set Matching (PSM) problems, in which a client aims to determine whether a collection of sets owned by a server matches her interest. Existing privacy-preserving cryptographic primitives cannot solve PSM problems efficiently without harming privacy. We propose a new modular framework that enables designers to build privacy-friendly PSM systems that output one bit: whether a server set or collection of server sets matches the client's set, while guaranteeing privacy of client and server sets. The communication cost of our protocols scales linearly with the size of the client's set and is independent of the number of server sets and their total size. We demonstrate the potential of our framework by designing and implementing novel solutions for two real-world PSM problems: determining whether a dataset has chemical compounds of interest, and determining whether a document collection has relevant documents. Our evaluation shows that our privacy gain comes at a reasonable communication and computation cost.
翻译:我们引入了私密配对(PSM)问题, 客户在其中旨在确定服务器拥有的数据集集是否与其利益相符; 现有的隐私保存加密原始材料无法在不损害隐私的情况下有效解决PSM问题。 我们提议一个新的模块框架,使设计者能够建立能够产生一个部分的隐私友好的PSM系统: 服务器集或服务器集,是否与客户集相匹配,同时保障客户集和服务器集的隐私。 我们协议的通信成本线性与客户集的大小成线,与服务器集数及其总大小无关。 我们通过设计和实施两个真实世界的 PSM问题的新解决方案,展示了我们框架的潜力: 确定数据集是否含有相关化学化合物, 以及确定文件集是否有相关文件。 我们的评估表明,我们的隐私收益是以合理的通信和计算成本获得的。