Disclosure-Compliant Query Answering
Summary: Mascara implements flexible disclosure policies via data masking and query rewriting. A relative-entropy utility model selects disclosure-compliant query with minimal information loss, achieving >90% success and sub-300ms overhead. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Rudi Poepsel-Lemaitre (Berlin Institute for the Foundations of Learning and Data; Technical University of Berlin)
- 2. Kaustubh Beedkar (Indian Institute of Technology Delhi)
- 3. Volker Markl (Berlin Institute for the Foundations of Learning and Data; German National Research Center for Information Technology; Technical University of Berlin)
BibTeX Citation
@inproceedings{poepsellemaitre_sigmod24,
title = {{Disclosure-Compliant Query Answering}},
author = {Poepsel-Lemaitre, Rudi and Beedkar, Kaustubh and Markl, Volker},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3698808},
url = {https://dl.acm.org/doi/10.1145/3698808},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,618 | Aegis: A Correlation-Based Data Masking Advisor for Data-Sharing Ecosystems | 2026 | SIGMOD | 4.9605343e-05 |
| 11,492 | Algorithmic Data Minimization for Machine Learning over Internet-of-Things Data Streams | 2025 | VLDB | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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