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dc.contributor.authorPhan, Q-S
dc.contributor.authorMalacaria, P
dc.contributor.authorASIA CCS '14 Proceedings of the 9th ACM symposium on Information, computer and communications security
dc.date.accessioned2014-09-16T08:57:50Z
dc.date.issued2014
dc.date.issued2014
dc.identifier.isbn978-1-4503-2800-5
dc.identifier.urihttp://qmro.qmul.ac.uk/jspui/handle/123456789/6120
dc.descriptionacmid: 2590328 keywords: model checking, quantitative information flow, satisfiability modulo theories, symbolic execution location: Kyoto, Japan numpages: 10
dc.description.abstractWe present a novel method for Quantitative Information Flow analysis. We show how the problem of computing information leakage can be viewed as an extension of the Satisfiability Modulo Theories (SMT) problem. This view enables us to develop a framework for QIF analysis based on the framework DPLL(T) used in SMT solvers. We then show that the methodology of Symbolic Execution (SE) also fits our framework. Based on these ideas, we build two QIF analysis tools: the first one employs CBMC, a bounded model checker for ANSI C, and the second one is built on top of Symbolic PathFinder, a Symbolic Executor for Java. We use these tools to quantify leaks in industrial code such as C programs from the Linux kernel, a Java tax program from the European project HATS, and anonymity protocols
dc.format.extent283 - 292 (9)
dc.publisherACM
dc.subjectmodel checking
dc.subjectquantitative information flow
dc.subjectsatisfiability modulo theories
dc.subjectsymbolic execution
dc.titleAbstract Model Counting: A Novel Approach for Quantification of Information Leaks
dc.typeConference Proceeding
dc.identifier.doi10.1145/2590296.2590328
pubs.organisational-group/Queen Mary University of London
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Electronic Engineering and Computer Science - Computer Science - Research Students
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Electronic Engineering and Computer Science - Staff
pubs.organisational-group/Queen Mary University of London/Faculty Reporting - Research Students
pubs.organisational-group/Queen Mary University of London/Faculty Reporting - Research Students/Faculty of Science & Engineering PGRs
pubs.publication-statusPublished
pubs.publisher-urlhttp://doi.acm.org/10.1145/2590296.2590328


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