Split Federated Learning for Secure Iot Applications : Concepts, Frameworks, Applications and Case Studies

Lingua: inglese

Editore: Institution Of Engineering & Technology Okt 2024, 2024

1839539453 / 9781839539459

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

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Descrizione dell’articolo da parte del venditore

Neuware - New approaches in federated learning and split learning have the potential to significantly improve ubiquitous intelligence in internet of things (IoT) applications. In split federated learning, the machine learning model is divided into smaller network segments, with each segment trained independently on a server using distributed local client data. The split learning method mitigates two fundamental drawbacks of federated learning: affordability, and privacy and security. When running machine learning computation on devices with limited resources, assigning only a portion of the network to train at the client-side minimizes the processing burden, compared to running a complete network as in federated learning. In addition, neither client nor server has full access to the other, which is more secure. This book reviews cutting edge technologies and advanced research in split federated learning. Coverage includes approaches to realizing and evaluating the effectiveness and advantages of federated learning and split-fed learning, the role of this technology in advancing and securing IoTs, advanced research on emerging AI models for preserving the privacy of the data owned by the clients, and the analysis and development of AI mechanisms in IoT architectures and applications. The use of split federated learning in natural language processing, recommendation systems, healthcare systems, emotion detection, smart agriculture, smart transportation and smart cities is discussed. Split Federated Learning for Secure IoT Applications: Concepts, frameworks, applications and case studies offers useful insights to the latest developments in the field for researchers, engineers and scientists in academia and industry, who are working in computing, AI, data science and cybersecurity with a focus on federated learning, machine learning and deep learning.…

Codice articolo 9781839539459

Titolo
Split Federated Learning for Secure Iot Applications : Concepts, Frameworks, Applications and Case Studies
Autore
Hong Lin
Editore
Institution Of Engineering & Technology Okt 2024
Anno di pubblicazione
2024
Condizione
Neu
Rilegatura
Buch
Lingua
inglese
ISBN 10
1839539453
ISBN 13
9781839539459
Peso dell'articolo
581 grammi
Dimensioni
234x156x18 mm

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 7 a 10 giorni lavorativiDa 5 a 7 giorni lavorativi
Primo articoloEUR 35,00EUR 45,00
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