V3DB: Audit-on-Demand Zero-Knowledge Proofs for Verifiable Vector Search over Committed Snapshots
Summary: V3DB provides audit-on-demand zero-knowledge proofs that IVF-PQ top-k results follow fixed semantics over a committed snapshot, hiding embeddings and index contents. Multiset checks avoid costly sorting and random access, enabling practical proving with millisecond verification. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Zipeng Qiu (Hong Kong University of Science and Technology)
- 2. Wenjie Qu (National University of Singapore)
- 3. Jiaheng Zhang (National University of Singapore)
- 4. Binhang Yuan (Hong Kong University of Science and Technology)
BibTeX Citation
@article{qiu_vldb26,
title = {{V3DB: Audit-on-Demand Zero-Knowledge Proofs for Verifiable Vector Search over Committed Snapshots}},
author = {Qiu, Zipeng and Qu, Wenjie and Zhang, Jiaheng and Yuan, Binhang},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {10},
pages = {2604--2626},
doi = {10.14778/3828612.3828618},
url = {https://doi.org/10.14778/3828612.3828618},
year = {2026}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,822 | ZKSQL: Verifiable and Efficient Query Evaluation with Zero-Knowledge Proofs | 2023 | VLDB | 6.3943931e-05 |
| 7,091 | PoneglyphDB: Efficient Non-interactive Zero-Knowledge Proofs for Arbitrary SQL-Query Verification | 2025 | SIGMOD | 5.601767e-05 |
| 7,646 | FedVSE: A Privacy-Preserving and Efficient Vector Search Engine for Federated Databases | 2025 | VLDB | 5.4772833e-05 |
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