GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel

The existing work has conducted in-depth research and analysis on global differential privacy (GDP) and local differential privacy (LDP) based on information theory. However, the data privacy preserving community does not systematically review and analyze GDP and LDP based on the information-theoret...

Full description

Bibliographic Details
Main Authors: Hai Liu, Changgen Peng, Youliang Tian, Shigong Long, Feng Tian, Zhenqiang Wu
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/24/3/430
_version_ 1797446541983612928
author Hai Liu
Changgen Peng
Youliang Tian
Shigong Long
Feng Tian
Zhenqiang Wu
author_facet Hai Liu
Changgen Peng
Youliang Tian
Shigong Long
Feng Tian
Zhenqiang Wu
author_sort Hai Liu
collection DOAJ
description The existing work has conducted in-depth research and analysis on global differential privacy (GDP) and local differential privacy (LDP) based on information theory. However, the data privacy preserving community does not systematically review and analyze GDP and LDP based on the information-theoretic channel model. To this end, we systematically reviewed GDP and LDP from the perspective of the information-theoretic channel in this survey. First, we presented the privacy threat model under information-theoretic channel. Second, we described and compared the information-theoretic channel models of GDP and LDP. Third, we summarized and analyzed definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP under their channel models. Finally, we discussed the open problems of GDP and LDP based on different types of information-theoretic channel models according to the above systematic review. Our main contribution provides a systematic survey of channel models, definitions, privacy-utility metrics, properties, and mechanisms for GDP and LDP from the perspective of information-theoretic channel and surveys the differential privacy synthetic data generation application using generative adversarial network and federated learning, respectively. Our work is helpful for systematically understanding the privacy threat model, definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP from the perspective of information-theoretic channel and promotes in-depth research and analysis of GDP and LDP based on different types of information-theoretic channel models.
first_indexed 2024-03-09T13:42:57Z
format Article
id doaj.art-1cb7ae2646aa46728501da5a5e40d836
institution Directory Open Access Journal
issn 1099-4300
language English
last_indexed 2024-03-09T13:42:57Z
publishDate 2022-03-01
publisher MDPI AG
record_format Article
series Entropy
spelling doaj.art-1cb7ae2646aa46728501da5a5e40d8362023-11-30T21:04:20ZengMDPI AGEntropy1099-43002022-03-0124343010.3390/e24030430GDP vs. LDP: A Survey from the Perspective of Information-Theoretic ChannelHai Liu0Changgen Peng1Youliang Tian2Shigong Long3Feng Tian4Zhenqiang Wu5Guizhou Big Data Academy, Guizhou University, Guiyang 550025, ChinaGuizhou Big Data Academy, Guizhou University, Guiyang 550025, ChinaCollege of Computer Science and Technology, Guizhou University, Guiyang 550025, ChinaCollege of Computer Science and Technology, Guizhou University, Guiyang 550025, ChinaSchool of Computer Science, Shaanxi Normal University, Xi’an 710119, ChinaSchool of Computer Science, Shaanxi Normal University, Xi’an 710119, ChinaThe existing work has conducted in-depth research and analysis on global differential privacy (GDP) and local differential privacy (LDP) based on information theory. However, the data privacy preserving community does not systematically review and analyze GDP and LDP based on the information-theoretic channel model. To this end, we systematically reviewed GDP and LDP from the perspective of the information-theoretic channel in this survey. First, we presented the privacy threat model under information-theoretic channel. Second, we described and compared the information-theoretic channel models of GDP and LDP. Third, we summarized and analyzed definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP under their channel models. Finally, we discussed the open problems of GDP and LDP based on different types of information-theoretic channel models according to the above systematic review. Our main contribution provides a systematic survey of channel models, definitions, privacy-utility metrics, properties, and mechanisms for GDP and LDP from the perspective of information-theoretic channel and surveys the differential privacy synthetic data generation application using generative adversarial network and federated learning, respectively. Our work is helpful for systematically understanding the privacy threat model, definitions, privacy-utility metrics, properties, and mechanisms of GDP and LDP from the perspective of information-theoretic channel and promotes in-depth research and analysis of GDP and LDP based on different types of information-theoretic channel models.https://www.mdpi.com/1099-4300/24/3/430GDP vs. LDPinformation-theoretic channelRényi divergencemutual informationexpected distortion
spellingShingle Hai Liu
Changgen Peng
Youliang Tian
Shigong Long
Feng Tian
Zhenqiang Wu
GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel
Entropy
GDP vs. LDP
information-theoretic channel
Rényi divergence
mutual information
expected distortion
title GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel
title_full GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel
title_fullStr GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel
title_full_unstemmed GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel
title_short GDP vs. LDP: A Survey from the Perspective of Information-Theoretic Channel
title_sort gdp vs ldp a survey from the perspective of information theoretic channel
topic GDP vs. LDP
information-theoretic channel
Rényi divergence
mutual information
expected distortion
url https://www.mdpi.com/1099-4300/24/3/430
work_keys_str_mv AT hailiu gdpvsldpasurveyfromtheperspectiveofinformationtheoreticchannel
AT changgenpeng gdpvsldpasurveyfromtheperspectiveofinformationtheoreticchannel
AT youliangtian gdpvsldpasurveyfromtheperspectiveofinformationtheoreticchannel
AT shigonglong gdpvsldpasurveyfromtheperspectiveofinformationtheoreticchannel
AT fengtian gdpvsldpasurveyfromtheperspectiveofinformationtheoreticchannel
AT zhenqiangwu gdpvsldpasurveyfromtheperspectiveofinformationtheoreticchannel