Fuzzy Message Detection (FMD) is a recent cryptographic primitive invented by Beck et al. (CCS'21) where an untrusted server performs coarse message filtering for its clients in a recipient-anonymous way. In FMD - besides the true positive messages - the clients download from the server their cover messages determined by their false-positive detection rates. What is more, within FMD, the server cannot distinguish between genuine and cover traffic. In this paper, we formally analyze the privacy guarantees of FMD from three different angles. First, we analyze three privacy provisions offered by FMD: recipient unlinkability, relationship anonymity, and temporal detection ambiguity. Second, we perform a differential privacy analysis and coin a relaxed definition to capture the privacy guarantees FMD yields. Finally, we simulate FMD on real-world communication data. Our theoretical and empirical results assist FMD users in adequately selecting their false-positive detection rates for various applications with given privacy requirements.
翻译：模糊信件探测(FMD)是贝克等人(CCS'21)最近发明的加密原始(FMZY),其中一个不受信任的服务器以接收者匿名的方式为客户过滤粗粗的信息。在FMD中,除了真正的正面信息外,客户从服务器下载由虚假阳性检测率决定的封面信息。此外,在FMD中,服务器无法区分真实和覆盖流量。在本文中,我们从三个不同角度正式分析了FMD的隐私保障。首先,我们分析了FMD提供的三项隐私规定:接收者不可连接性、关系匿名性和时间探测模糊性。第二,我们进行了差异隐私分析,并提出了一个宽松的定义,以获取隐私保障FMD产量。最后,我们用真实世界通信数据模拟FMD。我们的理论和经验结果有助于FMD用户在满足隐私要求的各种应用程序中适当选择其虚假阳性检测率。
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