Publishing Attributed Social Graphs with Formal Privacy Guarantees
Summary: End-to-end DP for attributed social graphs, beyond structure-only coverage. Adapts existing models and adds a new one to generate realistic synthetic graphs with attributes, enabling end-to-end privacy-preserving workflow with proven utility. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zach Jorgensen
- 2. Ting Yu
- 3. Graham Cormode
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,102 | PrivAGS: Differentially Private Attributed Graph Synthesis | 2026 | SIGMOD | 4.1945683e-05 |
| 10,728 | Continuous Publication of Weighted Graphs with Local Differential Privacy | 2025 | VLDB | 4.1945683e-05 |
| 10,759 | PrivAGM: Secure Construction of Differentially Private Directed Attributed Graph Models on Decentralized Social Graphs | 2025 | VLDB | 4.1945683e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next