Personalized Privacy Protection in Big Data
Author | : Youyang Qu |
Publisher | : Springer Nature |
Total Pages | : 148 |
Release | : 2021-07-23 |
ISBN-10 | : 9789811637506 |
ISBN-13 | : 9811637504 |
Rating | : 4/5 (06 Downloads) |
Download or read book Personalized Privacy Protection in Big Data written by Youyang Qu and published by Springer Nature. This book was released on 2021-07-23 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.