Quantifying the Re-identification Risk in Published Process Models.

Karim Maatouk, Felix Mannhardt

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)


Event logs are the basis of process mining operations such as process discovery, conformance checking, and process optimization. Sensitive information may be obtained by adversaries when re-identifying individuals that relate to the traces of an event log. This re-identification risk is dependent on the assumed background information of an attacker. Multiple techniques have been proposed to quantify the re-identification risks for published event logs. However, in many scenarios there is no need to release the full event log, a discovered process model annotated with frequencies suffices. This raises the question on how to quantify the re-identification risk in published process models. We propose a method based on generating sample traces to quantify this risk for process trees annotated with frequencies. The method was applied on several real-life event logs and process trees discovered by Inductive Miner. Our results show that there can be still a significant re-identification risk when publishing a process tree; however, this risk is often lower than that for releasing the original event log.

Original languageEnglish
Title of host publicationProcess Mining Workshops - ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 - November 4, 2021, Revised Selected Papers
EditorsJorge Munoz-Gama, Xixi Lu
Number of pages13
ISBN (Electronic)978-3-030-98580-6
ISBN (Print)9783030985806
Publication statusPublished - 2022

Publication series

NameLecture Notes in Business Information Processing (LNBIP)
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Bibliographical note

DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.


  • Process discovery
  • Process mining
  • Re-identification Risk


Dive into the research topics of 'Quantifying the Re-identification Risk in Published Process Models.'. Together they form a unique fingerprint.

Cite this