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A firm foundation for private data analysis

A firm foundation for private data analysis review articles Doi:10.1145/1866739.1866758 What does it mean to preserve privacy? BY cYnthia DWoRk a firm foundation for Private Data analysis associated with failure to control access to information, to control the flow of information, or to control the purposes for which information is employed. Differential privacy arose in a context in which ensuring privacy is a challenge even if all these control problems are solved: privacy-preserving statistical analysis of data. The problem of statistical disclosure control ” revealing accurate statistics about a set of respondents while preserving the privacy of individuals ”has a venerable history, with an extensive literature spanning statistics, theoretical computer science, security, databases, and cryptography (see, for example, the excellent survey of Adam and Wortmann,1 the discussion of related work in Blum et al.,2 and the Journal of Official Statistics dedicated to confidentiality and disclosure control). communications of th e ac m | ja n ua ry 2 0 1 1 | vo l . 5 4 | n o. 1 This long history is a testament to the importance of the problem. Statistical databases can be of enormous social value; they are used for apportioning resources, evaluating medical therapies, understanding the spread of disease, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Communications of the ACM Association for Computing Machinery

A firm foundation for private data analysis

Communications of the ACM , Volume 54 (1) – Jan 1, 2011

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References (32)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2011 by ACM Inc.
ISSN
0001-0782
DOI
10.1145/1866739.1866758
Publisher site
See Article on Publisher Site

Abstract

review articles Doi:10.1145/1866739.1866758 What does it mean to preserve privacy? BY cYnthia DWoRk a firm foundation for Private Data analysis associated with failure to control access to information, to control the flow of information, or to control the purposes for which information is employed. Differential privacy arose in a context in which ensuring privacy is a challenge even if all these control problems are solved: privacy-preserving statistical analysis of data. The problem of statistical disclosure control ” revealing accurate statistics about a set of respondents while preserving the privacy of individuals ”has a venerable history, with an extensive literature spanning statistics, theoretical computer science, security, databases, and cryptography (see, for example, the excellent survey of Adam and Wortmann,1 the discussion of related work in Blum et al.,2 and the Journal of Official Statistics dedicated to confidentiality and disclosure control). communications of th e ac m | ja n ua ry 2 0 1 1 | vo l . 5 4 | n o. 1 This long history is a testament to the importance of the problem. Statistical databases can be of enormous social value; they are used for apportioning resources, evaluating medical therapies, understanding the spread of disease,

Journal

Communications of the ACMAssociation for Computing Machinery

Published: Jan 1, 2011

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