Article (Scientific journals)
Publishing Community-Preserving Attributed Social Graphs with a Differential Privacy Guarantee
Chen, Xihui; Mauw, Sjouke; Ramirez Cruz, Yunior
2020In Proceedings on Privacy Enhancing Technologies, 2020 (4), p. 131-152
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Keywords :
attributed social graphs; generative models; differential privacy; community detection
Abstract :
[en] We present a novel method for publishing differentially private synthetic attributed graphs. Our method allows, for the first time, to publish synthetic graphs simultaneously preserving structural properties, user attributes and the community structure of the original graph. Our proposal relies on CAGM, a new community-preserving generative model for attributed graphs. We equip CAGM with efficient methods for attributed graph sampling and parameter estimation. For the latter, we introduce differentially private computation methods, which allow us to release communitypreserving synthetic attributed social graphs with a strong formal privacy guarantee. Through comprehensive experiments, we show that our new model outperforms its most relevant counterparts in synthesising differentially private attributed social graphs that preserve the community structure of the original graph, as well as degree sequences and clustering coefficients.
Disciplines :
Computer science
Author, co-author :
Chen, Xihui ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Mauw, Sjouke ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Ramirez Cruz, Yunior ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
no
Language :
English
Title :
Publishing Community-Preserving Attributed Social Graphs with a Differential Privacy Guarantee
Publication date :
17 August 2020
Journal title :
Proceedings on Privacy Enhancing Technologies
ISSN :
2299-0984
Publisher :
Sciendo
Volume :
2020
Issue :
4
Pages :
131-152
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
FnR Project :
FNR11685812 - Privacy-preserving Publication Of Dynamic Social Network Data In The Presence Of Active Adversaries, 2017 (01/06/2018-31/05/2021) - Yunior Ramirez-cruz
Available on ORBilu :
since 17 October 2020

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