Reference : A Scalable and Accurate Hybrid Vulnerability Analysis Framework

	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/10993/21897

Title :	A Scalable and Accurate Hybrid Vulnerability Analysis Framework
Language :	English
Author, co-author :	Thome, Julian [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2015
Main document title :	Doctoral Symposium co-located with 26th IEEE International Symposium on Software Reliability Engineering (2015)
Peer reviewed :	Yes
Audience :	International
Event name :	Doctoral Symposium co-located with 26th IEEE International Symposium on Software Reliability Engineering (2015)
Event date :	04-11-2015
Keywords :	[en] Software Security Assurance ; Vulnerability Analysis ; Program Analysis ; Symbolic Execution ; Constraint Solving ; Machine Learning
Abstract :	[en] Software security assurance is an important process in software development that protects the sensitive data and resources contained in and controlled by the software. Addressing security vulnerabilities at an early phase could decrease the cost of addressing them in later stages by two orders of magnitude. In order to detect vulnerabilities in Web services and Web applications in a scalable and accurate manner, we aim at developing a hybrid vulnerability analysis framework which combines program analysis, symbolic execution and machine learning. We use program analysis to identify potential vulnerable execution branches within the source code for the purpose of guiding the symbolic execution along the potentially vulnerable execution paths. We also propose scalable constraint solving techniques for vulnerability analysis. To further enhance scalability and accuracy, we also apply machine learning by incorporating predictors for identifying potentially vulnerable paths of the program based on known vulnerable cases.
Research centres :	SnT - Interdisciplinary Centre for Security, Reliability and Trust
Funders :	National Research Fund, Luxembourg (FNR/P10/03 and FNR9132112)
Name of the research project :	A Scalable and Accurate Hybrid Vulnerability Analysis Framework
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/21897
FnR project :	FnR ; FNR9132112 > Julian Thomé > HyVAn > A Scalable and Accurate Hybrid Vulnerability Analysis Framework > 01/09/2014 > 14/04/2018 > 2014

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