PrivAGS: Differentially Private Attributed Graph Synthesis
Summary: PrivAGS is an RDP-based framework for publishing synthetic attributed graphs by reconstructing topology and attributes using community-aware models, introducing MCEG to capture clustering structure. It preserves attribute correlations via a bounded Gaussian threshold mechanism and optimized probabilistic inference for high utility. (summarized by gpt-5-mini on Feb 11 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. SHUZHAN YE
- 2. LU CHEN
- 3. ZHIKUN ZHANG
- 4. YUNJUN GAO
- 5. YUXIANG WANG
- 6. XIAOLIANG XU
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 224 | CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies | 2004 | SIGMOD | 0.00032746205 |
| 453 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB | 0.00022741848 |
| 803 | Towards Identity Anonymization on Graphs | 2008 | SIGMOD | 0.00016478924 |
| 1,764 | PriView: Practical Differentially Private Release of Marginal Contingency Tables | 2014 | SIGMOD | 0.00010636626 |
| 3,161 | K-Automorphism: A General Framework for Privacy Preserving Network Publication | 2009 | VLDB | 7.4613905e-05 |
| 6,410 | Publishing Attributed Social Graphs with Formal Privacy Guarantees | 2016 | SIGMOD | 5.0753667e-05 |
Previous
Page 1 / 1
Next