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Protecting Privacy in Digital Records: The Potential of Privacy-Enhancing Technologies

Published: 08 January 2024 Publication History

Abstract

With increased concerns about data protection and privacy over the past several years, and concomitant introduction of regulations restricting access to personal information (PI), archivists in many jurisdictions now must undertake ‘sensitivity reviews’ of archival documents to determine whether they can make those documents accessible to researchers. Such reviews are onerous given increasing volume of records and complex due to how difficult it can be for archivists to identify whether records contain PI under the provisions of various laws. Despite research into the application of tools and techniques to automate sensitivity reviews, effective solutions remain elusive. Not yet explored as a solution to the challenge of enabling access to archival holdings subject to privacy restrictions is the application of privacy-enhancing technologies (PETs) —a class of emerging technologies that rest on the assumption that a body of documents is confidential or private and must remain so. While seemingly being counterintuitive to apply PETs to making archives more accessible, we argue that PETs could provide an opportunity to protect PI in archival holdings whilst still enabling research on those holdings. In this article, to lay a foundation for archival experimentation with use of PETs, we contribute an overview of these technologies based on a scoping review and discuss possible use cases and future research directions.

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cover image Journal on Computing and Cultural Heritage
Journal on Computing and Cultural Heritage   Volume 16, Issue 4
December 2023
473 pages
ISSN:1556-4673
EISSN:1556-4711
DOI:10.1145/3615351
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 January 2024
Online AM: 27 November 2023
Accepted: 14 September 2023
Revised: 25 August 2023
Received: 05 March 2023
Published in JOCCH Volume 16, Issue 4

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Author Tags

  1. Privacy-enhancing technologies
  2. homomorphic encryption
  3. trusted execution environments
  4. secure multiparty computation
  5. personal data stores
  6. privacy-preserving machine learning
  7. synthetic data

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  • Research-article

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  • Social Sciences and Humanities Research Council of Canada (SSHRC)
  • Blockchain and Distributed Ledger Technologies Training Program
  • University of British Columbia
  • Natural Science and Engineering Research Council of Canada

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