Methods for Reducing Disclosure Risks When Sharing Data:
Resources for Further Research
There is a growing
researchers working on statistical disclosure limitation
methods. The sources on previous pages provide good entry
points into this literature. Here, we describe additional
resources for further investigation.
Journals that frequently publish on privacy and confidentiality
Journal of Privacy and
of Official Statistics
on Data Privacy
journals have published special issues devoted entirely to
Statistica Neerlandica (1992, no. 2)
Journal of Official Statistics (1993 no. 2; 1998 no. 4)
Statistics and Computing (2003, no. 4)
Chance Magazine (2004, no. 4)
2. Monographs on privacy and confidentiality
These monographs contain research papers on confidentiality protection approaches.
The articles in these monographs are representative of research and practice in statistical disclosure limitation.
3. Websites with technical papers on privacy and confidentiality
J. and Saygin Y., eds. (2008) Privacy in Statistical
Databases 2008. Lecture Notes in Computer Science (5262), Springer.
Domingo Ferrer, J. and Franconi, L. eds. (2006), Privacy in
Statistical Databases 2006. Lecture Notes in Computer
Doyle, P., J. Lane, J. Theeuwes, and L.
Zayatz, eds. (2002), Confidentiality,
Disclosure Control and Data Access: Theory and Practical Applications,
Amsterdam, The Netherlands: Elsevier
Institute of Statistical Sciences Digital Government Project Website
workshops on data confidentiality
National Research Council reports: search "Information
Security and Privacy"
University of Michigan Population Studies Center research on confidentiality issues in data collection
Federal Committee on Statistical Methodology conference papers
Software for protecting microdata (mu-argus) and tabular data (tau-argus) from Statistics Netherlands.
4. Bibliographies on privacy and confidentiality
References on disclosure protection methods compiled by Bill
Winkler (as of 2008).
5. Readings for selected topics in statistical disclosure limitation
Quantifying disclosure risks:
-- Reiter J (2005), "Estimating risks of identification disclosure for microdata," Journal of the American Statistical Association, 100, 1103 - 1113.
-- Skinner C and Shlomo N (2008), "Assessing identification risk in survey microdata using log-linear models," Journal of the American Statistical Association, 103, 989 - 1001.
Quantifying data usefulness:
-- Karr AF, Kohnen CN, Oganian A, Reiter JP, and Sanil AP (2006), "A framework for evaluating the utility of data altered to protect confidentiality," The American Statistician, 60, 224 - 232.
-- Fienberg SE and McIntyre J. (2004). "Data swapping: Variations on a theme by Dalenius and Reiss," In Privacy in Statistical Databases: PSD 2004 Proceedings (Josep Domingo-Ferrer and VicenÁ Torra, eds.), Lecture Notes in Computer Science, Volume 3050, Springer-Verlag, 14-29.
-- The NISS data swapping toolkit.
-- Yancey WE, Winkler WE, and Creecy RH (2002), "Disclosure risk assessment in perturbative microdata protection," In Inference Control in Statistical Databases 2002: 135-152.
-- Defays D (1997), "Protecting micro-data by micro-aggregation: The experiences in Eurostat," Questiio, 21, 221 - 231.
Multiple imputation for disclosure limitation:
-- Reiter, JP (2008), "Protecting data confidentiality in public release datasets: Approaches based on multiple imputation," The Imputation Bulletin, 8.2, 1 - 6. (Link to paper).
-- The Survey of Income and Program Participation synthetic data project (Link to project website).
-- Kirkendall, N. and Sande, G. (1998) "Comparison of systems implementing automated cell suppression for economic statistics," Journal of Official Statistics, 14:513-535.