论文标题
私人收集匹配协议
Private Collection Matching Protocols
论文作者
论文摘要
我们介绍了私人集合匹配（PCM）问题，其中客户端旨在确定服务器拥有的集合是否与他们的兴趣相匹配。现有的隐私加密原始图无法在不损害隐私的情况下有效地解决PCM问题。我们提出了一个模块化框架，该框架使设计人员能够构建一个输出一位的PCM系统：服务器集合集合是否与客户端的集合相匹配。协议的通信成本与客户端集的大小线性扩展，并且独立于服务器元素的数量。我们通过为两个现实世界中的PCM问题设计和实施新的解决方案来证明我们的框架潜力：确定数据集是否具有感兴趣的化学化合物，并确定文档收集是否具有相关文档。我们的评估表明，我们以合理的沟通和计算成本提供了有关现有作品的隐私收益。
We introduce Private Collection Matching (PCM) problems, in which a client aims to determine whether a collection of sets owned by a server matches their interests. Existing privacy-preserving cryptographic primitives cannot solve PCM problems efficiently without harming privacy. We propose a modular framework that enables designers to build privacy-preserving PCM systems that output one bit: whether a collection of server sets matches the client's set. The communication cost of our protocols scales linearly with the size of the client's set and is independent of the number of server elements. We demonstrate the potential of our framework by designing and implementing novel solutions for two real-world PCM problems: determining whether a dataset has chemical compounds of interest, and determining whether a document collection has relevant documents. Our evaluation shows that we offer a privacy gain with respect to existing works at a reasonable communication and computation cost.
