國立虎尾科技大學 |

AI, blockchain and self-sovereign identity in higher education

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	AI, blockchain and self-sovereign identity in higher education/ edited by Hamid Jahankhani ... [et al.].
其他作者:	Jahankhani, Hamid.
出版者:	Cham :Springer Nature Switzerland : : 2023.,
面頁冊數:	vi, 313 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Higher Education. -
電子資源:	https://doi.org/10.1007/978-3-031-33627-0
ISBN:	9783031336270

AI, blockchain and self-sovereign identity in higher education
AI, blockchain and self-sovereign identity in higher education[electronic resource] /edited by Hamid Jahankhani ... [et al.]. - Cham :Springer Nature Switzerland :2023. - vi, 313 p. :ill. (some col.), digital ;24 cm. - Advanced sciences and technologies for security applications,2363-9466. - Advanced sciences and technologies for security applications..

1. The Role of Blockchain with a Cybersecurity Maturity Model in the Governance of Higher Education Supply Chains -- 2. Fighting the Tide - GPT and An Alarming Sense of Déjà Vu -- 3. Embedding AI in Higher Education: a call for a service design approach -- 4. An empirical study into Ransomware campaigns against the Education Sector & adopting the Cybersecurity Maturity Model Certification Framework -- 5. Strategic Decision-Making for Pedagogical Course Planning using NLP in Social Media -- 6. The Use of Virtual Learning Environments in Higher Education - Content, Community and Connectivism - Learning From Student Users -- 7. Influence of Artificial Intelligence in Higher Education; Impact, Risk and Counter Measure -- 8. Development of a Decentralized Personal Indefinable information (PII) management systems using Blockchain DBFT consensus Algorithm -- 9. Security Framework for Big Data usage in cloud-based e-learning application -- 10. A proactive approach to protect cloud computing environment against a Distributed Denial of Service (DDoS) attack.

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.

ISBN: 9783031336270

Standard No.: 10.1007/978-3-031-33627-0doiSubjects--Topical Terms:

679030
Higher Education.

LC Class. No.: LB1028.43

Dewey Class. No.: 378.0028563

AI, blockchain and self-sovereign identity in higher education
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520 $a 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.
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