Téléchargez le livre : Federated Cyber Intelligence

Federated Cyber Intelligence

Federated Learning for Cybersecurity de

,

Éditeur :

Springer


Paru le : 2025-04-23

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Description

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.
Pages
111 pages
Collection
n.c
Parution
2025-04-23
Marque
Springer
EAN papier
9783031865916
EAN PDF
9783031865923
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
2929 Ko
Prix
52,74 €
EAN EPUB
9783031865923
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
2079 Ko
Prix
52,74 €

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