私人重拳手的轻量级技术

D. Boneh, Elette Boyle, Henry Corrigan-Gibbs, N. Gilboa, Y. Ishai
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引用次数: 67

摘要

本文提出了一种解决私人大人物问题的新协议。在这个问题中,有许多客户机和一小组数据收集服务器。每个客户端持有一个私有位串。服务器希望在不了解任何客户端字符串的情况下恢复所有流行字符串的集合。例如,网络浏览器供应商可以使用我们的协议来找出哪些主页是受欢迎的,而无需了解任何用户的主页。我们还考虑了更简单的私有子集直方图问题,在这个问题中,服务器想要计算在一个特定集合中有多少客户端持有字符串,而不向客户端透露这个集合。我们的协议使用两个数据收集服务器,在协议运行时,每个客户端只向服务器发送一条消息。我们的协议保护客户端隐私,防止其中一个服务器的任意不当行为,我们的方法不需要公钥加密(安全通道除外),也不需要通用的多方计算。相反,我们依赖增量分布式点函数,这是一种新的加密工具,它允许客户端简洁地秘密共享指数级大二叉树节点上的标签,前提是该树具有单个非零路径。在此过程中,我们开发了新的通用工具,用于在分布式点函数的应用程序中提供恶意安全性。我们的重量级协议的一个限制是,它向服务器显示的信息比流行字符串集本身稍微多一些。我们精确地定义和量化了这种泄漏,并解释了如何改善其影响。在对位于美国两端的两台服务器进行的实验评估中,服务器可以在54分钟内从40万个客户端持有的256位字符串中找到200个最受欢迎的字符串。我们的协议是高度并行的。我们估计,每个逻辑服务器有20台物理机器,我们的协议可以在一个多小时的计算中计算超过1000万个客户机。
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Lightweight Techniques for Private Heavy Hitters
This paper presents a new protocol for solving the private heavy-hitters problem. In this problem, there are many clients and a small set of data-collection servers. Each client holds a private bitstring. The servers want to recover the set of all popular strings, without learning anything else about any client’s string. A web-browser vendor, for instance, can use our protocol to figure out which homepages are popular, without learning any user’s homepage. We also consider the simpler private subset-histogram problem, in which the servers want to count how many clients hold strings in a particular set without revealing this set to the clients.Our protocols use two data-collection servers and, in a protocol run, each client send sends only a single message to the servers. Our protocols protect client privacy against arbitrary misbehavior by one of the servers and our approach requires no public-key cryptography (except for secure channels), nor general-purpose multiparty computation. Instead, we rely on incremental distributed point functions, a new cryptographic tool that allows a client to succinctly secret-share the labels on the nodes of an exponentially large binary tree, provided that the tree has a single non-zero path. Along the way, we develop new general tools for providing malicious security in applications of distributed point functions.A limitation of our heavy-hitters protocol is that it reveals to the servers slightly more information than the set of popular strings itself. We precisely define and quantify this leakage and explain how to ameliorate its effects. In an experimental evaluation with two servers on opposite sides of the U.S., the servers can find the 200 most popular strings among a set of 400,000 client-held 256-bit strings in 54 minutes. Our protocols are highly parallelizable. We estimate that with 20 physical machines per logical server, our protocols could compute heavy hitters over ten million clients in just over one hour of computation.
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