Téléchargez le livre : Security and Privacy in Federated Learning

Security and Privacy in Federated Learning

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Éditeur :

Springer


Paru le : 2023-03-10

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168,79 €
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Description

In this book, the authors highlight the latest research findings on the security and privacy of federated learning systems. The main attacks and counterattacks in this booming field are presented to readers in connection with inference, poisoning, generative adversarial networks, differential privacy, secure multi-party computation, homomorphic encryption, and shuffle, respectively.   
The book offers an essential overview for researchers who are new to the field, while also equipping them to explore this “uncharted territory.” For each topic, the authors first present the key concepts, followed by the most important issues and solutions, with appropriate references for further reading. 
The book is self-contained, and all chapters can be read independently. It offers a valuable resource for master’s students, upper undergraduates, Ph.D. students, and practicing engineers alike.
Pages
133 pages
Collection
n.c
Parution
2023-03-10
Marque
Springer
EAN papier
9789811986918
EAN PDF
9789811986925
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
13
Taille du fichier
4823 Ko
Prix
168,79 €
EAN EPUB
9789811986925
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
13
Taille du fichier
11776 Ko
Prix
168,79 €

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