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Security and Privacy in Federated Learning

-15% su kodu: ENG15
230,37 
Įprasta kaina: 271,02 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
230,37 
Įprasta kaina: 271,02 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 271.0200 InStock
Nemokamas pristatymas į paštomatus per 11-15 darbo dienų užsakymams nuo 20,00 

Knygos aprašymas

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.

Informacija

Autorius: Lei Cui, Shui Yu,
Leidėjas: Springer Nature Singapore
Išleidimo metai: 2024
Knygos puslapių skaičius: 148
ISBN-10: 9811986940
ISBN-13: 9789811986949
Formatas: 235 x 155 x 8 mm. Knyga minkštu viršeliu
Kalba: Anglų

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