Synonyms
Confidentiality protection; Multiplicity; Privacy protection; Restricted data; Risk-utility tradeoff
Definition
Statistical Disclosure Limitation refers to the broad array of methods used to protect confidentiality of statistical data, i.e., fulfilling an obligation to data providers or respondents not to transmit their information to an unauthorized party. Data Access refers to complementary obligations of statistical agencies and others to provide information for statistical purposes without violating promises of confidentiality.
Historical Background
Starting in the early twentieth century, U.S. government statistical agencies worked to develop approaches for the protection of the confidentiality of data gathered on individuals and organizations. As such agencies also have a public obligation to use the data for the public good, they have developed both a culture of confidentiality protection and a set of statistical techniques to assure that data are released in a form...
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Abramovich F, Benjamini Y, Donoho D, Johnstone I. Adapting to unknown sparsity by controlling the false discovery rate. Ann Stat. 2006;34(2):584–653.
Anderson M, William SW. Challenges to the confidentiality of U.S. federal statistics, 1910–1965. J Off Stat. 2007;23(1):1–34.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Statist Soc B. 1995;57(1):289–300.
Dalenius T. Towards a methodology for statistical disclosure control. Statist Tidskrift. 1977;5(429–444): 2–1.
Donoho D, Jin J. Higher Criticism for detecting sparse heterogeneous mixtures. Ann Stat. 2004;32(3):962–94.
Doyle P, Lane JL, Theeuwes Jules JM, Zayatz LV, editors. Confidentiality, disclosure and data access: theory and practical application for statistical agencies. New York: Elsevier; 2001.
Fienberg SE. Confidentiality, privacy and disclosure limitation. In: Encyclopedia of social measurement, vol. 1. San Diego: Academic Press; 2005. p. 463–9.
Fienberg SE, Makov UE. Confidentiality, uniqueness and disclosure limitation for categorical data. J Off Stat. 1998;14(4):485–502.
Fienberg SE, Makov UE, Sanil AP. A Bayesian approach to data disclosure: optimal intruder behavior for continuous data. J Off Stat. 1997;13(1):75–89.
Fienberg SE, Makov UE, Steele RJ. Disclosure limitation using perturbation and related methods for categorical data (with discussion). J Off Stat. 1998;14(4):485–502.
Fienberg SE, Slavkovic AB. Preserving the confidentiality of categorical statistical databases when releasing information for association rules. Data Min Knowl Discov. 2005;11(2):155–80.
Hertzog TN, Scheuren FJ, Winkler WE. Data quality and record linkage techniques. New York: Springer-Verlag; 2007.
Lambert D. Measures of disclosure risk and harm. J Off Stat. 1993;9(2):313–31.
Raghunathan TE, Reiter J, Rubin DB. Multiple imputation for statistical disclosure limitation. J Off Stat. 2003;19(1):1–16.
Warren S, Brandeis L. The right to privacy. Harvard Law Rev. 1890;4(5):193–220.
Willenborg L, de Waal T. Elements of statistical disclosure control, vol. 155. New-York: Lecture Notes in Statistics Springer-Verlag; 2001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Fienberg, S.E., Jin, J. (2018). Statistical Disclosure Limitation for~Data~Access. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1046
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1046
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering