Federated Cyber Intelligence
Federated Learning for Cybersecurity
Springer
ISBN 978-3-031-86591-6
Standardpreis
Bibliografische Daten
Fachbuch
Buch. Softcover
2025
2 s/w-Abbildungen, 10 Farbabbildungen.
In englischer Sprache
Umfang: ix, 111 S.
Format (B x L): 15,5 x 23,5 cm
Verlag: Springer
ISBN: 978-3-031-86591-6
Weiterführende bibliografische Daten
Das Werk ist Teil der Reihe: SpringerBriefs in Computer Science
Produktbeschreibung
The subsequent sections offer insight into key cybersecurity concepts, including confidentiality, integrity, and availability. It also offers various types of cyber threats, such as malware, phishing, and advanced persistent threats. This book provides a practical guide to applying federated learning in areas such as intrusion detection, malware detection, phishing prevention, and threat intelligence sharing. It examines the unique challenges and solutions associated with this approach, such as data heterogeneity, synchronization strategies and privacy-preserving techniques.
This book concludes with discussions on emerging trends, including blockchain, edge computing and collaborative threat intelligence. This book is an essential resource for researchers, practitioners and decision-makers in cybersecurity and AI.
Autorinnen und Autoren
Kundeninformationen
Provides a practical guide to federated learning and the ever-evolving needs of cybersecurity professionals Offers insights into modern cyber threats, while proposing federated learning-based solutions Explores the interactions of federated learning and advances in cybersecurity and collaborative intelligence
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