Tabrizchi / Aghasi

Federated Cyber Intelligence

Federated Learning for Cybersecurity

Springer

ISBN 978-3-031-86591-6

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53,49 €

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auch verfügbar als eBook (PDF) für 53,49 €

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

auch verfügbar als eBook (PDF) für 53,49 €

Produktbeschreibung

This book offers a detailed exploration of how federated learning can address critical challenges in modern cybersecurity. It begins with an introduction to the core principles of federated learning. Then it highlights a strong foundation by exploring the fundamental components, workflow, and algorithms of federated learning, alongside its historical development and relevance in safeguarding digital systems.

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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