Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Process mining in industrial control systems
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-3371-6075
Independent researcher.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-2936-4185
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.ORCID iD: 0000-0002-9315-9920
2022 (English)In: 2022 IEEE 20th International Conference on Industrial Informatics (INDIN), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we discuss how process mining techniques can be applied in industrial control systems for modeling, verification, and enhancement of the cyber-physical system based on recorded data logs. Process mining is used for extracting the process models in different notations from the recorded behavioral traces of the system. The output model of the system’s behavior is mainly derived using an open-source tool called ProM. The model can be used for such applications as anomaly detection, detection of cyber-attacks and alarm analysis in industrial control systems with the help of various control flow discovery algorithms. The extracted process model can be used to verify how the event log deviates from it by replaying the log on Petri net for conformance analysis.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022. p. 1-6
Keywords [en]
Cyber-physical automation systems, IEC 61499, Process mining
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-95166DOI: 10.1109/INDIN51773.2022.9976111ISI: 000907121600001Scopus ID: 2-s2.0-85145780587OAI: oai:DiVA.org:ltu-95166DiVA, id: diva2:1724092
Conference
IEEE 20th International Conference on Industrial Informatics (INDIN’22), Perth, Australia [Online], July 25-28, 2022
Funder
EU, Horizon 2020, 871743 1-SWARM
Note

ISBN for host publication: 978-1-7281-7568-3

Available from: 2023-01-05 Created: 2023-01-05 Last updated: 2024-03-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Xavier, MidhunPatil, SandeepVyatkin, Valeriy

Search in DiVA

By author/editor
Xavier, MidhunPatil, SandeepVyatkin, Valeriy
By organisation
Computer Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 74 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf