Doquet: Differentially Oblivious Range and Join Queries with Private Data Structures
Summary: Doquet is the first differentially oblivious TEE framework supporting private indices, range selection, foreign-key/many-to-many joins, and select-join composition despite eavesdropped private-memory accesses. Proven DO and evaluated on SGX, it achieves up to 10× speedups over oblivious alternatives. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lina Qiu (Boston University)
- 2. Georgios Kellaris (Lerna AI)
- 3. Nikos Mamoulis (University of Ioannina)
- 4. Kobbi Nissim (Georgetown University)
- 5. George Kollios (Boston University)
BibTeX Citation
@article{qiu_vldb23,
title = {{Doquet: Differentially Oblivious Range and Join Queries with Private Data Structures}},
author = {Qiu, Lina and Kellaris, Georgios and Mamoulis, Nikos and Nissim, Kobbi and Kollios, George},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {13},
pages = {4160--4173},
doi = {10.14778/3625054.3625055},
url = {https://doi.org/10.14778/3625054.3625055},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,488 | OBIR-tree: An Efficient Oblivious Index for Spatial Keyword Queries on Secure Enclaves | 2025 | SIGMOD | 5.5102404e-05 |
| 8,427 | Femur: A Flexible Framework for Fast and Secure Querying from Public Key-Value Store | 2025 | SIGMOD | 5.3324907e-05 |
| 10,449 | Differentially Oblivious Multi-way Join | 2026 | SIGMOD | 4.9769913e-05 |
| 11,225 | SPECIAL: SynoPsis AssistEd Secure CollaboratIve AnaLytics | 2025 | VLDB | 4.9769913e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 121 | Boosting the Accuracy of Differentially Private Histograms Through Consistency | 2010 | VLDB | 0.0003107472 |
| 558 | Understanding Hierarchical Methods for Differentially Private Histograms | 2013 | VLDB | 0.0001646292 |
| 1,324 | PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions | 2016 | SIGMOD | 0.00011018143 |
| 1,530 | A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy | 2014 | VLDB | 0.00010345019 |
| 2,020 | Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations | 2019 | VLDB | 9.1714694e-05 |
| 2,076 | Efficient Oblivious Database Joins | 2020 | VLDB | 9.0798814e-05 |
| 2,456 | Towards Practical Oblivious Join | 2022 | SIGMOD | 8.4350645e-05 |
| 3,902 | Adore: Differentially Oblivious Relational Database Operators | 2023 | VLDB | 6.9311667e-05 |
| 5,639 | Practical Differential Privacy via Grouping and Smoothing | 2013 | VLDB | 6.0541959e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 9,345 | OBSCURE: Information-Theoretic Oblivious and Verifiable Aggregation Queries | 2019 | VLDB |
| 2 | 5,124 | Secure Query Processing with Data Interoperability in a Cloud Database Environment | 2014 | SIGMOD |
| 3 | 7,299 | Architecting a Differentially Private SQL Engine | 2019 | CIDR |
| 4 | 3,902 | Adore: Differentially Oblivious Relational Database Operators | 2023 | VLDB |
| 5 | 1,331 | A Privacy-Preserving Index for Range Queries | 2004 | VLDB |
| 6 | 2,456 | Towards Practical Oblivious Join | 2022 | SIGMOD |
| 7 | 2,076 | Efficient Oblivious Database Joins | 2020 | VLDB |
| 8 | 11,756 | Cracking-Like Join for Trusted Execution Environments | 2023 | VLDB |
| 9 | 11,642 | DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System | 2024 | VLDB |
| 10 | 10,449 | Differentially Oblivious Multi-way Join | 2026 | SIGMOD |