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PRIPEL: Privacy-preserving event log publishing including contextual information
Fahrenkrog-Petersen, Stephan A.
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Aa, Han van der
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Weidlich, Matthias
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DOI:
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https://doi.org/10.1007/978-3-030-58666-9_7
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URL:
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https://link.springer.com/chapter/10.1007%2F978-3-...
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Additional URL:
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https://arxiv.org/pdf/2006.12856.pdf
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Document Type:
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Conference or workshop publication
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Year of publication:
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2020
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Book title:
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Business process management : 18th International Conference, BPM 2020, Seville, Spain, September 13–18, 2020, proceedings
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The title of a journal, publication series:
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Lecture Notes in Computer Science
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Volume:
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12168
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Page range:
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111-128
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Conference title:
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BPM 2020
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Location of the conference venue:
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Online
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Date of the conference:
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13.-18.09.2020
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Publisher:
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Fahland, Dirk
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Ghidini, Chiara
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Becker, Jörg
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Dumas, Marlon
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Place of publication:
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Berlin [u.a.]
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Publishing house:
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Springer
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ISBN:
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978-3-030-58665-2 , 3-030-58665-0 , 978-3-030-58666-9
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ISSN:
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0302-9743 , 1611-3349
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Artificial Intelligence Methods (Juniorprofessur) (van der Aa 2020-)
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Subject:
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004 Computer science, internet
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Abstract:
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Event logs capture the execution of business processes in terms of executed activities and their execution context. Since logs contain potentially sensitive information about the individuals involved in the process, they should be pre-processed before being published to preserve the individuals’ privacy. However, existing techniques for such pre-processing are limited to a process’ control-flow and neglect contextual information, such as attribute values and durations. This thus precludes any form of process analysis that involves contextual factors. To bridge this gap, we introduce PRIPEL, a framework for privacy-aware event log publishing. Compared to existing work, PRIPEL takes a fundamentally different angle and ensures privacy on the level of individual cases instead of the complete log. This way, contextual information as well as the long tail process behaviour are preserved, which enables the application of a rich set of process analysis techniques. We demonstrate the feasibility of our framework in a case study with a real-world event log.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
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