Advanced machine learning, AI, and cybersecurity in Web3: theoretical knowledge and practical application
In the evolving landscape of Web3, the use of advanced machine learning, artificial intelligence, and cybersecurity transforms industries through theoretical exploration and practical application. The integration of advanced machine learning and AI techniques promises enhanced security protocols, pr...
Gespeichert in:
Weitere Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Hershey, Pennsylvania
IGI Global
2024
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Schriftenreihe: | Advances in web technologies and engineering (AWTE) book series
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Schlagworte: | |
Online-Zugang: | DE-91 DE-1050 Volltext |
Zusammenfassung: | In the evolving landscape of Web3, the use of advanced machine learning, artificial intelligence, and cybersecurity transforms industries through theoretical exploration and practical application. The integration of advanced machine learning and AI techniques promises enhanced security protocols, predictive analytics, and adaptive defenses against the increasing number of cyber threats. However, these technological improvements also raise questions regarding privacy, transparency, and the ethical implications of AI-driven security measures. Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application explores theories and applications of improved technological techniques in Web 3.0. It addresses the challenges inherent to decentralization while harnessing the benefits offered by advances, thereby paving the way for a safer and more advanced digital era. Covering topics such as fraud detection, cryptocurrency, and data management, this book is a useful resource for computer engineers, financial institutions, security and IT professionals, business owners, researchers, scientists, and academicians. |
Beschreibung: | 1 Online-Ressource (359 Seiten) |
ISBN: | 9781668486887 |
DOI: | 10.4018/978-1-6684-8686-3 |
Internformat
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Datensatz im Suchindex
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discipline | Informatik Wirtschaftswissenschaften |
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indexdate | 2024-12-17T19:01:33Z |
institution | BVB |
isbn | 9781668486887 |
language | English |
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publisher | IGI Global |
record_format | marc |
series2 | Advances in web technologies and engineering (AWTE) book series |
spelling | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application Hadj Ahmed Bouarara, editor Advanced machine learning, artificial intelligence, and cybersecurity in Web3 Hershey, Pennsylvania IGI Global 2024 1 Online-Ressource (359 Seiten) txt rdacontent c rdamedia cr rdacarrier Advances in web technologies and engineering (AWTE) book series In the evolving landscape of Web3, the use of advanced machine learning, artificial intelligence, and cybersecurity transforms industries through theoretical exploration and practical application. The integration of advanced machine learning and AI techniques promises enhanced security protocols, predictive analytics, and adaptive defenses against the increasing number of cyber threats. However, these technological improvements also raise questions regarding privacy, transparency, and the ethical implications of AI-driven security measures. Advanced Machine Learning, AI, and Cybersecurity in Web3: Theoretical Knowledge and Practical Application explores theories and applications of improved technological techniques in Web 3.0. It addresses the challenges inherent to decentralization while harnessing the benefits offered by advances, thereby paving the way for a safer and more advanced digital era. Covering topics such as fraud detection, cryptocurrency, and data management, this book is a useful resource for computer engineers, financial institutions, security and IT professionals, business owners, researchers, scientists, and academicians. Artificial intelligence Computer networks Security measures Computer security Cyber intelligence (Computer security) Internet of things Security measures Internet Security measures Machine learning Bouarara, Hadj Ahmed 1990- edt Erscheint auch als Druck-Ausgabe 1668486865 Erscheint auch als Druck-Ausgabe 9781668486863 https://doi.org/10.4018/978-1-6684-8686-3 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application Artificial intelligence Computer networks Security measures Computer security Cyber intelligence (Computer security) Internet of things Security measures Internet Security measures Machine learning |
title | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application |
title_alt | Advanced machine learning, artificial intelligence, and cybersecurity in Web3 |
title_auth | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application |
title_exact_search | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application |
title_full | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application Hadj Ahmed Bouarara, editor |
title_fullStr | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application Hadj Ahmed Bouarara, editor |
title_full_unstemmed | Advanced machine learning, AI, and cybersecurity in Web3 theoretical knowledge and practical application Hadj Ahmed Bouarara, editor |
title_short | Advanced machine learning, AI, and cybersecurity in Web3 |
title_sort | advanced machine learning ai and cybersecurity in web3 theoretical knowledge and practical application |
title_sub | theoretical knowledge and practical application |
topic | Artificial intelligence Computer networks Security measures Computer security Cyber intelligence (Computer security) Internet of things Security measures Internet Security measures Machine learning |
topic_facet | Artificial intelligence Computer networks Security measures Computer security Cyber intelligence (Computer security) Internet of things Security measures Internet Security measures Machine learning |
url | https://doi.org/10.4018/978-1-6684-8686-3 |
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