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Personalized Privacy Protection in Big Data

-15% su kodu: ENG15
93,58 
Įprasta kaina: 110,09 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
93,58 
Įprasta kaina: 110,09 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 110.0900 InStock
Nemokamas pristatymas į paštomatus per 11-15 darbo dienų užsakymams nuo 20,00 

Knygos aprašymas

This book presents the data privacy protection which has been extensively applied in our current era of big data. However, research into big data privacy is still in its infancy. Given the fact that existing protection methods can result in low data utility and unbalanced trade-offs, personalized privacy protection has become a rapidly expanding research topic.
In this book, the authors explore emerging threats and existing privacy protection methods, and discuss in detail both the advantages and disadvantages of personalized privacy protection. Traditional methods, such as differential privacy and cryptography, are discussed using a comparative and intersectional approach, and are contrasted with emerging methods like federated learning and generative adversarial nets.
The advances discussed cover various applications, e.g. cyber-physical systems, social networks, and location-based services. Given its scope, the book is of interest to scientists, policy-makers, researchers, and postgraduates alike.

Informacija

Autorius: Youyang Qu, Shui Yu, Lei Cui, Mohammad Reza Nosouhi,
Serija: Data Analytics
Leidėjas: Springer Nature Singapore
Išleidimo metai: 2022
Knygos puslapių skaičius: 152
ISBN-10: 9811637520
ISBN-13: 9789811637520
Formatas: 235 x 155 x 9 mm. Knyga minkštu viršeliu
Kalba: Anglų

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