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Personalized Privacy Protection In Big Data eBook
idioma: inglês
Editor:
Springer Nature Singapore, julho de 2021 ‧
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72,86€
10% DESCONTO
CARTÃO
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DISPONIBILIDADE IMEDIATA
Ebook para ADE
SINOPSE
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.
DETALHES
| Propriedade | Descrição |
|---|---|
| ISBN: | 9789811637506 |
| Editor: | Springer Nature Singapore |
| Data de Lançamento: | julho de 2021 |
| Idioma: | Inglês |
| Tipo de produto: | eBook |
| Formato e Compatibilidade: | |
| Coleção: | Data Analytics |
| Classificação Temática: |
eBooks em Inglês
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|
| EAN: | 9789811637506 |
| Acessibilidade: | Ver características de acessibilidade indicadas pelo editor |
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