An algorithm for privacy-preserving distributed user statistics
An algorithm for privacy-preserving distributed user statistics
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DOI：
10.1016/j.comnet.2013.05.011
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发表时间：
2013-10
期刊：
影响因子：
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通讯作者：
Florian Tschorsch;Björn Scheuermann
中科院分区：
文献类型：
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作者：
Florian Tschorsch;Björn Scheuermann
在本文中，我们提出了一种隐私保护方法来确定连接到具有多个服务运营商的分布式互联网服务的一个或多个入口点的不同用户的数量。这个问题是由匿名网络Tor以及在估计Tor用户数量时出现的困难引起的。我们提出了一种基于概率数据结构的分布式用户计数方法，具有准确的估计和高水平的隐私保护。我们从一个相对幼稚的方法开始，分析它提供的隐私保护水平。随后，我们在所获得的见解的基础上改进了这一基线机制。为了评估所讨论技术的隐私属性，我们使用了一种新的概率分析方法，该方法比较攻击者的先验知识和后验知识。
In this paper, we propose a privacy-preserving method to determine the number of distinct users who connected to one or more entry points of a distributed Internet service with multiple service operators. The problem is motivated by the anonymization network Tor, and the difficulties that arise when aiming to estimate the number of Tor users. We present a way to perform distributed user counting with accurate estimates and a high level of privacy protection, based on a probabilistic data structure. We start from a relatively naive approach, and analyze the level of privacy protection that it provides. Subsequently, we improve on this baseline mechanism, building upon the gained insights. In order to assess the privacy properties of the discussed techniques, we use a novel probabilistic analysis approach which compares an attacker’s a priori and a posteriori knowledge.