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    Understanding and mitigating cyberfraud in Africa

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    Author(s)
    Akinbowale, Oluwatoyin E
    Mashigo, Mariann P
    Zerihun, Prof. Mulatu
    Language
    English
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    Abstract
    The book covers the overview of cyberfraud and the associated global statistics. It demonstrates practicable techniques that financial institutions can employ to make effective decisions geared towards cyberfraud mitigation. Furthermore, the book contains some emerging technologies, such as information and communication technologies (ICT), forensic accounting, big data technologies, tools and analytics employed in fraud mitigation. In addition, it highlights the implementation of some techniques, such as the fuzzy analytical hierarchy process (FAHP) and system thinking approach to address information and security challenges. The book combines a case study, empirical findings, a systematic literature review and theoretical and conceptual concepts to provide practicable solutions to mitigate cyberfraud. The major contributions of this book include the demonstration of digital and emerging techniques, such as forensic accounting for cyber fraud mitigation. It also provides in-depth statistics about cyber fraud, its causes, its threat actors, practicable mitigation solutions, and the application of a theoretical framework for fraud profiling and mitigation.
    URI
    https://library.oapen.org/handle/20.500.12657/91185
    Keywords
    Cyberfraud;cyberspace;big data;fraud;fraud mitigation;forensic accounting;ICT;IT;information security;machine learning
    DOI
    10.4102/aosis.2024.BK485
    ISBN
    9781991269089, 9781991270085, 9781991271082
    Publisher
    AOSIS
    Publisher website
    https://books.aosis.co.za/index.php/ob
    Publication date and place
    Capetown, 2024
    Imprint
    AVARSITY Books
    Classification
    Technology: general issues
    Pages
    392
    Rights
    https://creativecommons.org/licenses/by-nc-nd/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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