A Demonstration of Sterling: A Privacy-Preserving Data Marketplace
Summary: Demonstrates Sterling, a decentralized, privacy-preserving data marketplace built with privacy-preserving smart contracts on a permissionless blockchain. Providers encode constraints (pricing, DP, use) and automated verification enforces them, enabling private analytics and ML with TEEs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nick Hynes
- 2. David Dao
- 3. David Yan
- 4. Raymond Cheng
- 5. Dawn Song
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,298 | Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms | 2019 | VLDB | 0.00012758104 |
| 6,262 | Fast Shapley Value Computation in Data Assemblage Tasks as Cooperative Simple Games | 2024 | SIGMOD | 5.1349507e-05 |
| 7,321 | Counterfactual Explanation of Shapley Value in Data Coalitions | 2024 | VLDB | 4.7629325e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 83 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00053933811 |
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