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Deep Federated Learning for Intelligent DDoS Intrusion Detection: A Secure, Scalable, and Privacy-Preserving Framework for DDoS Intrusion Detection Using Deep Federated Learning - Softcover

S, Manoranjitham

 
9786630199413: Deep Federated Learning for Intelligent DDoS Intrusion Detection: A Secure, Scalable, and Privacy-Preserving Framework for DDoS Intrusion Detection Using Deep Federated Learning
Softcover
ISBN 10: 6630199413 ISBN 13: 9786630199413
Verlag: LAP LAMBERT Academic Publishing, 2026

Inhaltsangabe

The rapid growth of fog-edge computing has introduced new cybersecurity challenges, particularly the increasing threat of Distributed Denial-of-Service (DDoS) attacks. Traditional intrusion detection systems often struggle to provide accurate, scalable, and privacy-preserving solutions in decentralized environments. This book presents a deep federated learning framework that enables collaborative model training without sharing sensitive data, ensuring enhanced privacy and robust threat detection. It explores the integration of deep learning techniques with federated learning to identify DDoS attacks efficiently across distributed fog-edge networks. The proposed framework emphasizes intelligent intrusion detection, improved detection accuracy, reduced communication overhead, and secure distributed learning. This book is intended for researchers, postgraduate students, cybersecurity professionals, and practitioners interested in artificial intelligence, network security, federated learning, and fog-edge computing, providing valuable insights into next-generation AI-driven cybersecurity solutions.

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Über die Autorin bzw. den Autor

Mrs. S. Manoranjitham, M.E., is an Assistant Professor in the Department of Information Technology. Her research interests include artificial intelligence, cybersecurity, federated learning, cloud and fog-edge computing. She is committed to advancing secure, intelligent, and privacy-preserving solutions through teaching and research.

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Verlag
LAP LAMBERT Academic Publishing
Erscheinungsdatum
2026
Sprache
Englisch
ISBN 10 
6630199413
ISBN 13 
9786630199413
Einband
Taschenbuch
Anzahl der Seiten
60
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
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