Personalized Privacy Protection in Big Data /
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 pr...
| Main Authors: | , , , |
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| Corporate Author: | |
| Format: | Book |
| Language: | English |
| Published: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2021
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| Edition: | 1st ed. 2021 |
| Series: | Computer Science (SpringerNature-11645)
Data analytics |
| Subjects: |
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| 245 | 1 | 0 | |a Personalized Privacy Protection in Big Data / |c by Youyang Qu, Mohammad Reza Nosouhi, Lei Cui, Shui Yu |
| 250 | |a 1st ed. 2021 | ||
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| 505 | 0 | |a Chapter 1: Introduction -- Chapter 2: Current Methods of Privacy Protection -- Chapter 3: Privacy Attacks -- Chapter 4: Personalize Privacy Defense -- Chapter 5: Future Directions -- Chapter6: Summary and Outlook | |
| 506 | |a Restricted for use by site license. | ||
| 520 | |a 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 | ||
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| 650 | 2 | 4 | |a Data Analysis and Big Data |
| 650 | 2 | 4 | |a Data Mining and Knowledge Discovery |
| 650 | 2 | 4 | |a Data Science |
| 650 | 2 | 4 | |a Principles and Models of Security |
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| 700 | 1 | |a Nosouhi, Mohammad Reza |e author. |1 https://orcid.org/0000-0001-6959-0975 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Yu, Shui, |e author |1 https://orcid.org/0000-0003-4485-6743 |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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