A software package for the application of probabilistic anonymisation to sensitive individual-level data: A proof of principle with an example from the ALSPAC birth cohort study

Journal article

Avraam, Demetris, Boyd, Andy, Goldstein, Harvey and Burton, Paul. (2018). A software package for the application of probabilistic anonymisation to sensitive individual-level data: A proof of principle with an example from the ALSPAC birth cohort study. Longitudinal and Life Course Studies. 9(4), pp. 433-446. https://doi.org/10.14301/llcs.v9i4.478

Authors	Avraam, Demetris, Boyd, Andy, Goldstein, Harvey and Burton, Paul
Abstract	Individual-level data require protection from unauthorised access to safeguard confidentiality and security of sensitive information. Risks of disclosure are evaluated through privacy risk assessments and are controlled or minimised before data sharing and integration. The evolution from ‘Micro Data Laboratory’ traditions (i.e. access in controlled physical locations) to ‘Open Data’ (i.e. sharing individual-level data) drives the development of efficient anonymisation methods and protection controls. Effective anonymisation techniques should increase the uncertainty surrounding re-identification while retaining data utility, allowing informative data analysis. ‘Probabilistic anonymisation’ is one such technique, which alters the data by addition of random noise. In this paper, we describe the implementation of one probabilistic anonymisation technique into an operational software written in R and we demonstrate its applicability through application to analysis of asthma-related data from the ALSPAC cohort study. The software is designed to be used by data managers and users without the requirement of advanced statistical knowledge.
Keywords	probabilistic anonymisation; disclosure control; measurement error; h-rank index; ALSPAC
Year	2018
Journal	Longitudinal and Life Course Studies
Journal citation	9 (4), pp. 433-446
Publisher	Society for Longitudinal and Life Course Studies
ISSN	1757-9597
Digital Object Identifier (DOI)	https://doi.org/10.14301/llcs.v9i4.478
Scopus EID	2-s2.0-85061775904
Open access	Open access
Research or scholarly	Research
Page range	433-446
Research Group	Institute for Learning Sciences and Teacher Education (ILSTE)
Author's accepted manuscript	AM_Avraam_2018_A_software_package_for_the_application.pdf File Access Level Open
Publisher's version	License All rights reserved File Access Level Controlled
Output status	Published
Additional information	This record includes a post-peer-review, pre-copy edited version of an article published in Longitudinal and Life Course Studies. The definitive publisher-authenticated version Avraam, D., Boyd, A., Goldstein, H., & Burton, P. (2018). A software package for the application of probabilistic anonymisation to sensitive individual-level data: a proof of principle with an example from the ALSPAC birth cohort study. Longitudinal and Life Course Studies, 9(4), 433-446, is available at: doi:http://dx.doi.org/10.14301/llcs.v9i4.478
Place of publication	United Kingdom

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