Privacy risk assessment in context: a meta-model based on contextual integrity.

Henriksen-Bulmer, Jane; Faily, Shamal; Jeary, Sheridan

Abstract

Publishing data in open format is a growing trend, particularly for public bodies who have a legal obligation to make data available as open data. We look at the privacy implications of publishing open data and, in particular, how organisations can make informed decisions around privacy risks in relation to open data publishing before publication occurs. Using a well established theoretical privacy assessment framework, Contextual Integrity, we illustrate how this can be translated into a practical meta-model that can assist public bodies in assessing what privacy implications or risks might be associated with making a particular dataset available as open data. We validate the meta-model by providing a worked example and illustrate the effectiveness of this by reference to a case study application where the meta-model was successfully applied in practice.

Citation

HENRIKSEN-BULMER, J., FAILY, S. and JEARY, S. 2019. Privacy risk assessment in context: a meta-model based on contextual integrity. Computers and security [online], 82, pages 270-283. Available from: https://doi.org/10.1016/j.cose.2019.01.003

• Journal Article Type: Article
• Acceptance Date: Jan 6, 2019
• Online Publication Date: Jan 11, 2019
• Publication Date: May 31, 2019
• Deposit Date: Sep 16, 2021
• Publicly Available Date: Nov 23, 2021
• Journal: Computers and security
• Print ISSN: 0167-4048
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 82
• Pages: 270-283
• DOI: https://doi.org/10.1016/j.cose.2019.01.003
• Keywords: Open data; Personal data; Data protection; Privacy and computing; Information governance; Public sector; Systems security
• Public URL: https://rgu-repository.worktribe.com/output/1427938