A deterministic approach for protecting privacy in sensitive personal data

Avraam, Demetris ORCID: 0000-0001-8908-2441, Jones, Elinor and Burton, Paul (2022) A deterministic approach for protecting privacy in sensitive personal data. BMC MEDICAL INFORMATICS AND DECISION MAKING, 22 (1). 24-.

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Official URL: http://dx.doi.org/10.1186/s12911-022-01754-4

Abstract

<h4>Background</h4>Data privacy is one of the biggest challenges for any organisation which processes personal data, especially in the area of medical research where data include sensitive information about patients and study participants. Sharing of data is therefore problematic, which is at odds with the principle of open data that is so important to the advancement of society and science. Several statistical methods and computational tools have been developed to help data custodians and analysts overcome this challenge.<h4>Methods</h4>In this paper, we propose a new deterministic approach for anonymising personal data. The method stratifies the underlying data by the categorical variables and re-distributes the continuous variables through a k nearest neighbours based algorithm.<h4>Results</h4>We demonstrate the use of the deterministic anonymisation on real data, including data from a sample of Titanic passengers, and data from participants in the 1958 Birth Cohort.<h4>Conclusions</h4>The proposed procedure makes data re-identification difficult while minimising the loss of utility (by preserving the spatial properties of the underlying data); the latter means that informative statistical analysis can still be conducted.

Item Type:	Article
Uncontrolled Keywords:	Data privacy, Deterministic anonymisation, Disclosure risk, Information loss, k nearest neighbours
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Population Health
Depositing User:	Symplectic Admin
Date Deposited:	08 Feb 2023 16:01
Last Modified:	08 Feb 2023 16:02
DOI:	10.1186/s12911-022-01754-4
Open Access URL:	https://doi.org/10.1186/s12911-022-01754-4
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3168284