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dc.contributor.author
Liu, Alice Y.
dc.contributor.author
Müller, Samuel
dc.contributor.author
Xu, Ke
dc.date.accessioned
2017-06-08T15:34:03Z
dc.date.available
2017-06-08T15:34:03Z
dc.date.issued
2006
dc.identifier.uri
http://hdl.handle.net/20.500.11850/1605
dc.description.abstract
Regulatory compliance of business operations is a critical problem for enterprises. As enterprises increasingly use business process management systems to automate their business processes, technologies to automatically check compliance of process models against compliance rules are becoming important. In this paper, we present a method for improving the reliability and minimizing the risk of failure of business process management systems from a compliance perspective. The proposed method allows for the separate modeling of both process models and compliance concerns. Business process models expressed in the Business Process Execution Language are transformed into Pi calculus and then into Finite State Machines. Compliance rules captured in the graphical Business Property Specification Language are translated into Linear Temporal Logic. Thus, process models can be verified against these compliance rules by means of model checking technology. The benefit of our method is threefold: Through the automated verification of a large set of business process models, our approach increases deployment efficiency and lowers the risk of installing non-compliant processes. Furthermore, it reduces the cost associated with inspecting business process models for compliance. Finally, compliance checking may guarantee compliance of new process models before their execution and thereby increases the reliability of business operations in general.
dc.language.iso
en
dc.publisher
IBM
dc.subject
model transformation
dc.subject
compliance
dc.subject
compliance rule modeling
dc.subject
business process modeling
dc.subject
model checking
dc.title
A Static Compliance Checking Framework for Business Process Models
dc.type
Report
ethz.journal.title
IBM Research Technical Report
ethz.pages.start
RZ 3679
ethz.size
34 p.
ethz.notes
Also published in: IBM Systems Journal, Volume 46, Issue 2, pages 335-361, ISSN 0018-8670.
ethz.publication.place
Armonk, NY
ethz.publication.status
published
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02660 - Institut für Informationssicherheit::03634 - Basin, David / Basin, David
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02660 - Institut für Informationssicherheit::03634 - Basin, David / Basin, David
ethz.identifier.url
http://domino.research.ibm.com/library/cyberdig.nsf/papers/24F8C9826FFA455585257266003397F3/$File/RZ3679.pdf
ethz.date.deposited
2017-06-08T15:34:21Z
ethz.source
ECIT
ethz.identifier.importid
imp59364b420c8b986668
ethz.ecitpid
pub:11435
ethz.eth
yes
ethz.availability
Metadata only
ethz.rosetta.installDate
2017-07-26T21:23:02Z
ethz.rosetta.lastUpdated
2018-10-01T03:32:32Z
ethz.rosetta.versionExported
true
ethz.COinS
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