Privacy in Data Systems
Summary: Perturb individual records and reconstruct original value distributions to build decision-tree classifiers and enable association-rule mining with accuracy comparable to using raw data. Introduce “Hippocratic databases” — principles, challenges, and solution directions for embedding privacy responsibility into database systems. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Rakesh Agrawal (IBM)
BibTeX Citation
@inproceedings{agrawal_pods03,
address = {New York, NY, USA},
series = {{PODS} '03},
title = {{Privacy in Data Systems}},
url = {https://dl.acm.org/doi/10.1145/773153.773157},
doi = {10.1145/773153.773157},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Agrawal, Rakesh},
year = {2003}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 68 | Privacy-Preserving Data Mining | 2000 | SIGMOD | 0.00037958605 |
| 254 | On the Design and Quantification of Privacy Preserving Data Mining Algorithms | 2001 | PODS | 0.00023020039 |
| 411 | Hippocratic Databases | 2002 | VLDB | 0.00018699914 |
| 1,872 | Information Sharing Across Private Databases | 2003 | SIGMOD | 9.4632771e-05 |
| 2,933 | Watermarking Relational Databases | 2002 | VLDB | 7.8402509e-05 |
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