Data environment analysis and the key variable mapping system

Mark Elliot; Susan Lomax; Elaine Mackey; Kingsley Purdam

doi:10.1007/978-3-642-15838-4_13

Data environment analysis and the key variable mapping system

Mark Elliot, Susan Lomax, Elaine Mackey, Kingsley Purdam

Social Statistics

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

It is now generally accepted that the measurement of statistical disclosure risk should be carried out with reference to the data environment into which a proposed dataset is to be released. This is normally considered through the development of intrusion or attack scenarios. Elliot and Dale's (1999) scheme set out a general set of principles for a scenario analysis, the output of which was a set of key variables. In this paper we outline an empirically based method, Data Environment Analysis which operationalises these ideas and a prototype tool the Key Variable Mapping System which has been designed to produce lists of key variables, with much more precise specification than was previously possible. © 2010 Springer-Verlag Berlin Heidelberg.

Original language	English
Title of host publication	Privacy in Statistical Databases
Place of Publication	Berlin
Publisher	Springer Nature
Pages	138-147
Number of pages	9
Volume	6344
ISBN (Print)	3642158374, 9783642158377
DOIs	https://doi.org/10.1007/978-3-642-15838-4_13
Publication status	Published - 2010
Event	International Conference on Privacy in Statistical Databases, PSD 2010 - Corfu Duration: 1 Jul 2010 → …

Publication series

Name	Lecture Notes in Computer Science

Conference

Conference	International Conference on Privacy in Statistical Databases, PSD 2010
City	Corfu
Period	1/07/10 → …

Keywords

Data Environment
Key Variables
Scenarios
Statistical Disclosure Risk

Access to Document

10.1007/978-3-642-15838-4_13

Impact on the Statistical Confidentiality Practices of Data Stewardship Organisations
Elliot, M. (Participant), Purdam, K. (Participant), Mackey, E. (Participant), Smith, D. (Participant) & (Participant)
Impact: Economic impacts, Societal impacts, Legal impacts

Cite this

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AU - Lomax, Susan

AU - Mackey, Elaine

AU - Purdam, Kingsley

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AB - It is now generally accepted that the measurement of statistical disclosure risk should be carried out with reference to the data environment into which a proposed dataset is to be released. This is normally considered through the development of intrusion or attack scenarios. Elliot and Dale's (1999) scheme set out a general set of principles for a scenario analysis, the output of which was a set of key variables. In this paper we outline an empirically based method, Data Environment Analysis which operationalises these ideas and a prototype tool the Key Variable Mapping System which has been designed to produce lists of key variables, with much more precise specification than was previously possible. © 2010 Springer-Verlag Berlin Heidelberg.

KW - Data Environment

KW - Key Variables

KW - Scenarios

KW - Statistical Disclosure Risk

U2 - 10.1007/978-3-642-15838-4_13

DO - 10.1007/978-3-642-15838-4_13

M3 - Chapter

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SN - 9783642158377

VL - 6344

T3 - Lecture Notes in Computer Science

SP - 138

EP - 147

BT - Privacy in Statistical Databases

PB - Springer Nature

CY - Berlin

T2 - International Conference on Privacy in Statistical Databases, PSD 2010

Y2 - 1 July 2010

ER -

Data environment analysis and the key variable mapping system

Abstract

Publication series

Conference

Keywords

Access to Document

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Impacts

Impact on the Statistical Confidentiality Practices of Data Stewardship Organisations

Cite this