Membership Inference Attacks against GANs by Leveraging Over-representation Regions

Reference : Membership Inference Attacks against GANs by Leveraging Over-representation Regions


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/48640

Title :	Membership Inference Attacks against GANs by Leveraging Over-representation Regions
Language :	English
Author, co-author :	Hu, Hailong [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PI Mauw >]
	Pang, Jun [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Publication date :	2021
Main document title :	Proceedings of the 27th ACM SIGSAC Conference on Computer and Communications Security (CCS'21)
Publisher :	ACM
Pages :	2387-2389
Peer reviewed :	Yes
Audience :	International
Event name :	2021 ACM SIGSAC Conference on Computer and Communications Security (CCS)
Event date :	2021
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/48640
DOI :	10.1145/3460120.3485338
FnR project :	FnR ; FNR13550291 > Hailong Hu > PriML > Privacy Attacks And Protection In Machine Learning As A Service > 01/12/2019 > 30/11/2023 > 2019

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	File	Commentary	Version	Size	Access
Open access	CCS21.pdf		Publisher postprint	436.15 kB	View/Open

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