A Comprehensive Survey on Local Differential Privacy
Joint Authors
Niu, Xiaoguang
Cai, Zhaohui
Li, Dan
Xiong, Xingxing
Liu, Shubo
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-29, 29 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-08
Country of Publication
Egypt
No. of Pages
29
Main Subjects
Information Technology and Computer Science
Abstract EN
With the advent of the era of big data, privacy issues have been becoming a hot topic in public.
Local differential privacy (LDP) is a state-of-the-art privacy preservation technique that allows to perform big data analysis (e.g., statistical estimation, statistical learning, and data mining) while guaranteeing each individual participant’s privacy.
In this paper, we present a comprehensive survey of LDP.
We first give an overview on the fundamental knowledge of LDP and its frameworks.
We then introduce the mainstream privatization mechanisms and methods in detail from the perspective of frequency oracle and give insights into recent studied on private basic statistical estimation (e.g., frequency estimation and mean estimation) and complex statistical estimation (e.g., multivariate distribution estimation and private estimation over complex data) under LDP.
Furthermore, we present current research circumstances on LDP including the private statistical learning/inferencing, private statistical data analysis, privacy amplification techniques for LDP, and some application fields under LDP.
Finally, we identify future research directions and open challenges for LDP.
This survey can serve as a good reference source for the research of LDP to deal with various privacy-related scenarios to be encountered in practice.
American Psychological Association (APA)
Xiong, Xingxing& Liu, Shubo& Li, Dan& Cai, Zhaohui& Niu, Xiaoguang. 2020. A Comprehensive Survey on Local Differential Privacy. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-29.
https://search.emarefa.net/detail/BIM-1208615
Modern Language Association (MLA)
Xiong, Xingxing…[et al.]. A Comprehensive Survey on Local Differential Privacy. Security and Communication Networks No. 2020 (2020), pp.1-29.
https://search.emarefa.net/detail/BIM-1208615
American Medical Association (AMA)
Xiong, Xingxing& Liu, Shubo& Li, Dan& Cai, Zhaohui& Niu, Xiaoguang. A Comprehensive Survey on Local Differential Privacy. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-29.
https://search.emarefa.net/detail/BIM-1208615
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208615