On Optimizing the Trade-off between Privacy and Utility in Data Provenance
Summary: Formalizes privacy-utility trade-off in data provenance via provenance abstraction; privacy = queries matching obfuscated provenance (k-anonymity style), utility = entropy of the abstraction. Shows intractability; proposes greedy heuristics exploiting provenance structure and validates on TPC-H/IMDB. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Daniel Deutch (Tel Aviv University)
- 2. Ariel Frankenthal (Tel Aviv University)
- 3. Amir Gilad (Duke University)
- 4. Yuval Moskovitch (University of Michigan)
BibTeX Citation
@inproceedings{deutch_sigmod21,
title = {{On Optimizing the Trade-off between Privacy and Utility in Data Provenance}},
author = {Deutch, Daniel and Frankenthal, Ariel and Gilad, Amir and Moskovitch, Yuval},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3452835},
url = {https://dl.acm.org/doi/10.1145/3448016.3452835},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,881 | DPXPlain: Privately Explaining Aggregate Query Answers | 2023 | VLDB | 5.2567693e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 17 | Provenance Semirings | 2007 | PODS | 0.00059752575 |
| 391 | Why Not? | 2009 | SIGMOD | 0.00019238698 |
| 819 | Provenance for Aggregate Queries | 2011 | PODS | 0.00013666629 |
| 1,272 | Discovering Queries based on Example Tuples | 2014 | SIGMOD | 0.00011248674 |
| 1,345 | Reverse Engineering Complex Join Queries | 2013 | SIGMOD | 0.00010953079 |
| 2,679 | FastQRE: Fast Query Reverse Engineering | 2018 | SIGMOD | 8.1453935e-05 |
| 2,835 | Fine-Grained, Secure and Efficient Data Provenance on Blockchain Systems | 2019 | VLDB | 7.9553846e-05 |
| 3,349 | Reverse Engineering Aggregation Queries | 2017 | VLDB | 7.391292e-05 |
| 4,176 | Aggregation in Probabilistic Databases via Knowledge Compilation | 2012 | VLDB | 6.7573044e-05 |
| 6,538 | Provenance Views for Module Privacy | 2011 | PODS | 5.7534198e-05 |
| 7,234 | Hypothetical Reasoning via Provenance Abstraction | 2019 | SIGMOD | 5.5792063e-05 |
| 7,361 | Enabling Privacy in Provenance-Aware Workflow Systems | 2011 | CIDR | 5.5424891e-05 |
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