DBScholar

Back to papers

Small Domain Randomization: Same Privacy, More Utility

Summary: Introduces small domain randomization to improve utility in privacy-preserving data publishing. Partitions data into sub-tables with smaller sensitive-value domains, enabling higher retention probabilities and independent perturbation while preserving privacy bounds. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10300
Venue
VLDB
Year
2010
Pagerank
5.2634238e-05
Overall Rank
9,485 | 34.93%
DOI
10.14778/1920841.1920919

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{chaytor_vldb10,
        title = {{Small Domain Randomization: Same Privacy, More Utility}},
        author = {Chaytor, Rhonda and Wang, Ke},
        journal = {PVLDB},
        series = {{VLDB} '10},
        volume = {3},
        number = {1},
        pages = {608--619},
        doi = {10.14778/1920841.1920919},
        url = {https://doi.org/10.14778/1920841.1920919},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
12,326 Publishing Microdata with a Robust Privacy Guarantee 2012 VLDB 5.093636e-05
Previous Page 1 / 1 Next

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.

Previous Page 1 / 1 Next

Semantically Similar Papers