Personalized Privacy Protection in Big Data / by Youyang Qu, Mohammad Reza Nosouhi, Lei Cui, Shui Yu.

Format:

Book

Author/Creator:

Qu, Youyang., Author.

Nosouhi, Mohammad Reza., Author.

Cui, Lei, Author.

Yu, Shui, Author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Data analytics 2520-1867

Data Analytics, 2520-1867

Language:

English

Subjects (All):

Data protection-Law and legislation.

Quantitative research.

Data mining.

Artificial intelligence-Data processing.

Coding theory.

Information theory.

Computer security.

Privacy.

Data Analysis and Big Data.

Data Mining and Knowledge Discovery.

Data Science.

Coding and Information Theory.

Principles and Models of Security.

Local Subjects:

Privacy.

Data Analysis and Big Data.

Data Mining and Knowledge Discovery.

Data Science.

Coding and Information Theory.

Principles and Models of Security.

Physical Description:

1 online resource (XI, 139 pages) : 36 illustrations, 34 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-981-16-3750-6

9789811637506

Access Restriction:

Restricted for use by site license.