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    Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs


    Khalid, Muhammad Irfan, Ahmed, Mansoor and Kim, Jungsuk (2023) Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs. Sensors, 23 (17). p. 7604. ISSN 1424-8220

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    Abstract

    Dynamic consent management allows a data subject to dynamically govern her consent to access her data. Clearly, security and privacy guarantees are vital for the adoption of dynamic consent management systems. In particular, specific data protection guarantees can be required to comply with rules and laws (e.g., the General Data Protection Regulation (GDPR)). Since the primary instantiation of the dynamic consent management systems in the existing literature is towards developing sustainable e-healthcare services, in this paper, we study data protection issues in dynamic consent management systems, identifying crucial security and privacy properties and discussing severe limitations of systems described in the state of the art. We have presented the precise definitions of security and privacy properties that are essential to confirm the robustness of the dynamic consent management systems against diverse adversaries. Finally, under those precise formal definitions of security and privacy, we have proposed the implications of state-of-the-art tools and technologies such as differential privacy, blockchain technologies, zero-knowledge proofs, and cryptographic procedures that can be used to build dynamic consent management systems that are secure and private by design.
    Item Type: Article
    Keywords: data protection; dynamic consent management; security; privacy by design; general data protection regulation (GDPR); differential privacy; blockchain;
    Academic Unit: Faculty of Social Sciences > Research Institutes > Innovation Value Institute, IVI
    Item ID: 18910
    Identification Number: 10.3390/s23177604
    Depositing User: IR Editor
    Date Deposited: 19 Sep 2024 14:57
    Journal or Publication Title: Sensors
    Publisher: MDPI AG
    Refereed: Yes
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/18910
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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