BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Edge-based blockchain enabled anomaly detection for insider attack prevention in Internet of Things

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    View/Open
    Awan_et_al_TETT (2.651Mb)
    Download
    Publication date
    2021-06
    Author
    Tukur, Y.M.
    Thakker, Dhaval
    Awan, Irfan U.
    Keyword
    Internet of Things (IoT)
    Edge-based blockchain enabled anomaly detection technique
    Insider attack prevention
    Edge computing
    Sequence-based anomaly detection
    Data
    Rights
    © 2020 John Wiley & Sons, Ltd. This is the peer reviewed version of the following article: Tukur YM, Thakker D and Awan IU (2021) Edge-based blockchain enabled anomaly detection for insider attack prevention in Internet of Things. Transactions on Emerging Telecommunications Technologies. 32(6): e4158., which has been published in final form at https://doi.org/10.1002/ett.4158. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
    Peer-Reviewed
    Yes
    Open Access status
    openAccess
    
    Metadata
    Show full item record
    Abstract
    Internet of Things (IoT) platforms are responsible for overall data processing in the IoT System. This ranges from analytics and big data processing to gathering all sensor data over time to analyze and produce long-term trends. However, this comes with prohibitively high demand for resources such as memory, computing power and bandwidth, which the highly resource constrained IoT devices lack to send data to the platforms to achieve efficient operations. This results in poor availability and risk of data loss due to single point of failure should the cloud platforms suffer attacks. The integrity of the data can also be compromised by an insider, such as a malicious system administrator, without leaving traces of their actions. To address these issues, we propose in this work an edge-based blockchain enabled anomaly detection technique to prevent insider attacks in IoT. The technique first employs the power of edge computing to reduce the latency and bandwidth requirements by taking processing closer to the IoT nodes, hence improving availability, and avoiding single point of failure. It then leverages some aspect of sequence-based anomaly detection, while integrating distributed edge with blockchain that offers smart contracts to perform detection and correction of abnormalities in incoming sensor data. Evaluation of our technique using real IoT system datasets showed that the technique remarkably achieved the intended purpose, while ensuring integrity and availability of the data which is critical to IoT success.
    URI
    http://hdl.handle.net/10454/18894
    Version
    Accepted manuscript
    Citation
    Tukur YM, Thakker D and Awan IU (2021) Edge-based blockchain enabled anomaly detection for insider attack prevention in Internet of Things. Transactions on Emerging Telecommunications Technologies. 32(6): e4158.
    Link to publisher’s version
    https://doi.org/10.1002/ett.4158
    Type
    Article
    Collections
    Engineering and Informatics Publications

    entitlement

     
    DSpace software (copyright © 2002 - 2022)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.