9786630199413 - deep federated learning for intelligent ddos intrusion detection: a secure, scalable, and privacy-preserving framework for ddos intrusion detection using deep federated learning di s, manoranjitham (5 risultati)
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 58,20
EUR 3,85 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 48,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 60 pp. Englisch.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 a…ccurate, 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. 60 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 48,90
EUR 60,54 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 ac…curate, 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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Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 42,55
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Deep Federated Learning for Intelligent DDoS Intrusion Detection | A Secure, Scalable, and Privacy-Preserving Framework for DDoS Intrusion Detection Using Deep Federated Learning | Manoranjitham S | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630199413 | Verantwortliche… Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
