Distributed Measurement with Private Set-Union Cardinality
Ellis Fenske, Akshaya Mani, Aaron Johnson, Micah Sherr
摘要
This paper introduces a cryptographic protocol for efficiently aggregating a count of unique items across a set of data parties privately -that is, without exposing any information other than the count. Our protocol allows for more secure and useful statistics gathering in privacy-preserving distributed systems such as anonymity networks; for example, it allows operators of anonymity networks such as Tor to securely answer the questions: how many unique users are using the distributed service? and how many hidden services are being accessed? We formally prove the correctness and security of our protocol in the Universal Composability framework against an active adversary that compromises all but one of the aggregation parties. We also show that the protocol provides security against adaptive corruption of the data parties, which prevents them from being victims of targeted compromise. To ensure safe measurements, we also show how the output can satisfy differential privacy. We present a proof-of-concept implementation of the private set-union cardinality protocol (PSC) and use it to demonstrate that PSC operates with low computational overhead and reasonable bandwidth. In particular, for reasonable deployment sizes, the protocol run at timescales smaller than the typical measurement period would be and thus is suitable for distributed measurement.
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引用它的顶会 Paper11
- Privacy-Preserving Dynamic Learning of Tor Network TrafficRob Jansen, Matthew Traudt, Nicholas HopperCCS 2018 · 被引用 26 次
- How to Make Private Distributed Cardinality Estimation Practical, and Get Differential Privacy for FreeChanghui Hu, Jin Li, Zheli Liu, Xiaojie Guo 等USENIX Security 2021 · 被引用 22 次
- Once is Never Enough: Foundations for Sound Statistical Inference in Tor Network ExperimentationRob Jansen, Justin Tracey, Ian GoldbergUSENIX Security 2021 · 被引用 21 次
- KVSAgg: Secure Aggregation of Distributed Key-Value SetsYuhan Wu, Siyuan Dong, Yi Zhou, Yikai Zhao 等ICDE 2023 · 被引用 8 次
- Investigating Security Folklore: A Case Study on the Tor over VPN PhenomenonMatthias Fassl, Alexander Ponticello, Adrian Dabrowski, Katharina KrombholzCSCW 2023 · 被引用 6 次
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