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Data Protection Fortification: An Agile Approach for Threat Analysis of IoT Data

Published: 05 January 2023 Publication History
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  • Abstract

    Data from Internet of Things (IoT) devices has become a critical asset for decision-making. However, IoT devices have security challenges due to their low-resource constraints, heterogeneity, and deployment in hostile environments. Systems consuming IoT data must thus be designed with security measures to detect and prevent data tampering attacks.
    We develop a data-centric threat modeling method named Data Protection Fortification (DPF) that practitioners can use during planning to assess and mitigate the security risk of using IoT data sources. We use design science to develop and validate DPF on 5 development teams from 3 organizations.
    Results show that DPF can be used to identify and improve security practices of data sources. Practitioners have a positive attitude towards using DPF and because it is easily understood, it has the potential to become a communication tool for security between developers and stakeholders.

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    Published In

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    IoT '22: Proceedings of the 12th International Conference on the Internet of Things
    November 2022
    259 pages
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 05 January 2023

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    Author Tags

    1. Data protection fortification
    2. Data-centric Threat analysis
    3. IoT
    4. Security
    5. Threat analysis

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    • Poster
    • Research
    • Refereed limited

    Funding Sources

    • The Research Council of Norway

    Conference

    IoT 2022

    Acceptance Rates

    Overall Acceptance Rate 28 of 84 submissions, 33%

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