A Protocol for Privately Reporting Ad Impressions at Scale
Matthew Green, Watson Ladd, Ian Miers
2016年份
78被引次数
20顶会引用
摘要
We present a protocol to enable privacy preserving advertising reporting at scale. Unlike previous systems, our work scales to millions of users and tens of thousands of distinct ads. Our approach builds on the homomorphic encryption approach proposed by Adnostic [42], but uses new cryptographic proof techniques to efficiently report billions of ad impressions a day using an additively homomorphic voting schemes. Most importantly, our protocol scales without imposing high loads on trusted third parties. Finally, we investigate a cost effective method to privately deliver ads with computational private information retrieval.
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引用它的顶会 Paper20
- PIR with Compressed Queries and Amortized Query ProcessingSebastian Angel, Hao Chen, Kim Laine, Srinath T. V. SettyS&P 2018 · 被引用 353 次
- Communication-Computation Trade-offs in PIRAsra Ali, Tancrède Lepoint, Sarvar Patel, Mariana Raykova 等USENIX Security 2021 · 被引用 126 次
- Addra: Metadata-private voice communication over fully untrusted infrastructureIshtiyaque Ahmad, Yuntian Yang, Divyakant Agrawal, Amr El Abbadi 等OSDI 2021 · 被引用 79 次
- Private Stateful Information RetrievalSarvar Patel, Giuseppe Persiano, Kevin YeoCCS 2018 · 被引用 76 次
- Single-Server Private Information Retrieval with Sublinear Amortized TimeHenry Corrigan-Gibbs, Alexandra Henzinger, Dmitry KoganEUROCRYPT 2022 · 被引用 64 次
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