Seeliger, Alexander ; Nolle, Timo ; Schmidt, Benedikt ; Mühlhäuser, Max (2016)
Process Compliance Checking using Taint Flow Analysis.
Dublin, Ireland
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Due to the growing complexity of processes, regulations, policies and guidelines (e.g., Sarbanes-Oxley-Act) computer-assisted business process analysis - known as process mining - is becoming more and more relevant for organisations. One discipline of process mining is backward compliance checking, which aims to detect non-compliant process variants based on historic data. Most existing approaches compare the "as-is" view with desired process models. However, most organisations do not maintain such models, making such approaches less attractive. This paper proposes a process flow analysis which uses graph-reachability to check whether the actual "as-is" process graph violates compliance constraints. Our approach is inspired by the taint flow algorithm which is used in code analysis to identify security vulnerabilities in software applications. We conducted a case study evaluating the compliance of event logs and performed a benchmark to show that our approach outperforms the LTL checker and the PetriNet pattern approach in ProM.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2016 |
Autor(en): | Seeliger, Alexander ; Nolle, Timo ; Schmidt, Benedikt ; Mühlhäuser, Max |
Art des Eintrags: | Bibliographie |
Titel: | Process Compliance Checking using Taint Flow Analysis |
Sprache: | Englisch |
Publikationsjahr: | 11 Dezember 2016 |
Verlag: | AIS |
Buchtitel: | Proceedings of the 37th International Conference on Information Systems (ICIS) |
Band einer Reihe: | 37 |
Veranstaltungsort: | Dublin, Ireland |
Zugehörige Links: | |
Kurzbeschreibung (Abstract): | Due to the growing complexity of processes, regulations, policies and guidelines (e.g., Sarbanes-Oxley-Act) computer-assisted business process analysis - known as process mining - is becoming more and more relevant for organisations. One discipline of process mining is backward compliance checking, which aims to detect non-compliant process variants based on historic data. Most existing approaches compare the "as-is" view with desired process models. However, most organisations do not maintain such models, making such approaches less attractive. This paper proposes a process flow analysis which uses graph-reachability to check whether the actual "as-is" process graph violates compliance constraints. Our approach is inspired by the taint flow algorithm which is used in code analysis to identify security vulnerabilities in software applications. We conducted a case study evaluating the compliance of event logs and performed a benchmark to show that our approach outperforms the LTL checker and the PetriNet pattern approach in ProM. |
ID-Nummer: | TUD-CS-2016-1455 |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Telekooperation LOEWE LOEWE > LOEWE-Schwerpunkte LOEWE > LOEWE-Schwerpunkte > NICER – Vernetzte infrastrukturlose Kooperation zur Krisenbewältigung |
Hinterlegungsdatum: | 31 Dez 2016 12:59 |
Letzte Änderung: | 14 Jun 2021 06:14 |
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