Spectrum: High-bandwidth Anonymous Broadcast
Zachary Newman, Sacha Servan-Schreiber, Srinivas Devadas
Abstract
We present Spectrum, a high-bandwidth, metadata-private file broadcasting system. In Spectrum, a small number of broadcasters share a file with many subscribers via two or more non-colluding broadcast servers. Subscribers generate cover traffic by sending dummy files, hiding which users are broadcasters and which users are only consumers.
Spectrum optimizes for a setting with few broadcasters and many subscribers-as is common to many real-world applications-to drastically improve throughput over prior work. Malicious clients are prevented from disrupting broadcasts using a novel blind access control technique that allows servers to reject malformed requests. Spectrum also prevents deanonymization of broadcasters by malicious servers deviating from protocol. Our techniques for providing malicious security are applicable to other systems for anonymous broadcast and may be of independent interest.
We implement and evaluate Spectrum. Compared to the state-of-the-art in cryptographic anonymous communication systems, Spectrum's peak throughput is 4-120,000× faster (and commensurately cheaper) in a broadcast setting. Deployed on two commodity servers, Spectrum allows broadcasters to share 1 GB (two full-length 720p documentary movies) in 13h 20m with an anonymity set of 10,000 (for a total cost of about $6.84). These costs scale roughly linearly in the size of the file and total number of users, and Spectrum parallelizes trivially with more hardware.
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Install the CLIlune papers fulltext f28f5a02-d56d-42ce-88fb-a3b1544021f7Cited by top-tier papers9
- Private Approximate Nearest Neighbor Search with Sublinear CommunicationSacha Servan-Schreiber, Simon Langowski, Srinivas DevadasS&P 2022 · 37 citations
- Boomerang: Metadata-Private Messaging under Hardware TrustPeipei Jiang, Qian Wang, Jianhao Cheng, Cong Wang et al.NSDI 2023 · 13 citations
- Abuse Reporting for Metadata-Hiding Communication Based on Secret SharingSaba EskandarianUSENIX Security 2024 · 9 citations
- Secure Vickrey Auctions for Online AdvertisingArchit Bhatnagar, Yunming Xiao, Ang Chen, Amrita Roy ChowdhuryNSDI 2026 · 1 citation
- Trellis: Robust and Scalable Metadata-private Anonymous BroadcastSimon Langowski, Sacha Servan-Schreiber, Srinivas DevadasNDSS 2023
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- Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep LearningPayap Sirinam, Mohsen Imani, Marc Juarez, Matthew WrightCCS 2018 · 632 citations
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- The Loopix Anonymity SystemAnia M. Piotrowska, Jamie Hayes, Tariq Elahi, Sebastian Meiser et al.USENIX Security 2017 · 214 citations
- Lightweight Techniques for Private Heavy HittersDan Boneh, Elette Boyle, Henry Corrigan-Gibbs, Niv Gilboa et al.S&P 2021 · 134 citations
- Fairness in an Unfair World: Fair Multiparty Computation from Public Bulletin BoardsArka Rai Choudhuri, Matthew Green, Abhishek Jain, Gabriel Kaptchuk et al.CCS 2017 · 130 citations
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