Search-based Test and Improvement of Machine-Learning-Based Anomaly Detection Systems

Reference : Search-based Test and Improvement of Machine-Learning-Based Anomaly Detection Systems


	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/10993/40033

Title :	Search-based Test and Improvement of Machine-Learning-Based Anomaly Detection Systems
Language :	English
Author, co-author :	Cordy, Maxime [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Muller, Steve []
	Papadakis, Mike [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC) >]
	Le Traon, Yves [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	2019
Main document title :	ACM SIGSOFT International Symposium on Software Testing and Analysis
Peer reviewed :	Yes
Audience :	International
Event name :	ACM SIGSOFT International Symposium on Software Testing and Analysis
Event date :	from 15-7-2019 to 19-7-2019
Research centres :	Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Security Design and Validation Research Group (SerVal)
Funders :	Fonds National de la Recherche - FnR
Name of the research project :	CODEMATES
Permalink :	http://hdl.handle.net/10993/40033
FnR project :	FnR ; FNR11686509 > Michail Papadakis > CODEMATES > COntinuous DEvelopment with Mutation Analysis and TESting > 01/09/2018 > 31/08/2021 > 2017

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Open access	issta19main-p399-p-ee7da60-41285M-submitted.pdf		Author postprint	780.29 kB	View/Open

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