Abstract
Existing access control mechanisms are not sufficient for data protection. They are only preventive and cannot guarantee that data is accessed for the intended purpose. This paper proposes a novel approach for multi-perspective conformance checking which considers the control-flow, data and privacy perspectives of a business process simultaneously to find the context in which data is processed. In addition to detecting deviations in each perspective, the approach is able to detect hidden deviations where non-conformity relates to either a combination of two or all three aspects of a business process. The approach has been implemented in the open source ProM framework and was evaluated through controlled experiments using synthetic logs of a simulated real-life process.
Original language | English |
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Title of host publication | Intelligent Information Systems - CAiSE Forum 2021, Proceedings |
Editors | Selmin Nurcan, Axel Korthaus |
Publisher | Springer |
Chapter | 10 |
Pages | 82-91 |
Number of pages | 10 |
ISBN (Electronic) | 978-3-030-79108-7 |
ISBN (Print) | 978-3-030-79107-0 |
DOIs | |
Publication status | Published - 15 Jun 2021 |
Publication series
Name | Lecture Notes in Business Information Processing |
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Volume | 424 LNBIP |
ISSN (Print) | 1865-1348 |
ISSN (Electronic) | 1865-1356 |
Funding
Acknowledgement. The author has received funding within the BPR4GDPR project from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 787149.
Keywords
- Conformance checking
- Data privacy
- Multi-layer alignment
- Multi-perspective analysis
- Process mining