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AI in Health and Social Care: A Methodology for Privacy Risk Modeling and Simulation

Published: 13 May 2024 Publication History
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  • Abstract

    As health and social care data networks evolve and adapt to greater digitalization and datafication of health, data and analytics systems are developing and bringing forward new ways to share, access and analyze data. Organizations and individuals making data sharing decisions for AI-enabled health and social care services need to be able to balance the benefits of such uses with the possible risks that may ensue - including those related to issues of privacy and security. In this paper, we provide an overview of our approach to privacy risk assessment for cross-domain access and re-use of sensitive data for research purposes using Spyderisk - an automated risk assessment tool. We apply Spyderisk to a real AI research scenario and consider the ways in which such techniques could support multiple stakeholders to assess privacy and security risks.

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    References

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        cover image ACM Conferences
        WWW '24: Companion Proceedings of the ACM on Web Conference 2024
        May 2024
        1928 pages
        ISBN:9798400701726
        DOI:10.1145/3589335
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Publication History

        Published: 13 May 2024

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        Author Tags

        1. automated risk analysis
        2. cause-and-effect
        3. data governance
        4. privacy risk assessment
        5. threat modelling

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        • NIHR Southampton Biomedical Research Centre (Data, Health and Society Theme)

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        WWW '24: The ACM Web Conference 2024
        May 13 - 17, 2024
        Singapore, Singapore

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