HADES: Range-Filtered Private Aggregation on Public Data
Summary: HADES is a one-round FHE protocol for private aggregation over public databases that hides predicate parameters (point, range, boolean) by deriving predicate indicators from plaintext records without extra trust setups. Uses elementwise-mapping and optimized reduction to fit FHE noise budgets; multi-threaded implementation yields 204–6574x speedups (TPC-H, 1M rows: 15h→38s). (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Xiaoyuan Liu
- 2. Ni Trieu
- 3. Trinabh Gupta
- 4. Ishtiyaque Ahmad
- 5. Dawn Song
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 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,146 | HEDA: Multi-Attribute Unbounded Aggregation over Homomorphically Encrypted Database | 2023 | VLDB | 9.4333516e-05 |
| 8,664 | Pantheon: Private Retrieval from Public Key-Value Store | 2023 | VLDB | 4.4721784e-05 |
Previous
Page 1 / 1
Next