AI, Blockchain and Self-Sovereign Identity in Higher Education

Hamid Jahankhani (Editor), Arshad Jamal (Editor), Guy Brown (Editor), Eustathios Sainidis (Editor), Rose Fong (Editor), Usman J. Butt (Editor)

    Research output: Book/ReportBookpeer-review

    Abstract

    This book aims to explore the next generation of online learning challenges including the security and privacy issues of digital transformation strategies that is required in teaching and learning. Also, what efforts does the industry need to invest in changing mind-sets and behaviours of both students and faculty members in adoption of virtual and blended learning?

    The book provides a comprehensive coverage of not only the technical and ethical issues presented by the use of AI, blockchain and self-sovereign identity, but also the adversarial application of AI and its associated implications. The authors recommend a number of novel approaches to assist in better detecting, thwarting and addressing AI challenges in higher education.

    The book provides a valuable reference for cyber security experts and practitioners, network security professionals and higher education strategist and decision-makers. It is also aimed at researchers seeking to obtain a more profound knowledge of machine learning and deep learning in the context of cyber security and AI in higher education. Each chapter is written by an internationally renowned expert who has extensive experience in industry or academia. Furthermore, this book blends advanced research findings with practice-based methods to provide the reader with advanced understanding and relevant skills.
    Original languageEnglish
    Place of PublicationCham, Switzerland
    PublisherSpringer
    Number of pages313
    Edition1st
    ISBN (Electronic)9783031336270
    ISBN (Print)9783031336263, 9783031336294
    DOIs
    Publication statusPublished - 23 Jun 2023

    Publication series

    NameAdvanced Sciences and Technologies for Security Applications
    PublisherSpringer
    ISSN (Print)1613-5113
    ISSN (Electronic)2363-9466

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