From Network Traffic Data to a Business-Level Event Log

Moshe Hadad, Gal Engelberg, Pnina Soffer

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

Abstract

Event logs are the main source for business process mining techniques. However, not all information systems produce a standard event log. Furthermore, logs may reflect only parts of the process which may span multiple systems. We suggest using network traffic data to fill these gaps. However, traffic data is interleaved and noisy, and there is a conceptual gap between this data and event logs at the business level. This paper proposes a method for producing event logs from network traffic data. The specific challenges addressed are (a) abstracting the low-level data to business-meaningful activities, (b) overcoming the interleaving of low-level events due to concurrency of activities and processes, and (c) associating the abstracted events to cases. The method uses two trained sequence models based on Conditional random fields (CRF), applied to data reflecting interleaved activities. We use simulated traffic data generated by a predefined business process. The data is annotated for sequence learning to produce models which are used for identifying concurrently performed activities and cases to produce an event log. The event log is conformed against the process models with high fitness and precision scores.

Original languageEnglish
Title of host publicationEnterprise, Business-Process and Information Systems Modeling - 24th International Conference, BPMDS 2023, and 28th International Conference, EMMSAD 2023, Proceedings
EditorsHan van der Aa, Dominik Bork, Henderik A. Proper, Rainer Schmidt
PublisherSpringer Science and Business Media Deutschland GmbH
Pages60-75
Number of pages16
ISBN (Print)9783031342400
DOIs
StatePublished - 2023
Event24th International Conference on Business Process Modeling, Development, and Support, BPMDS 2023 and 28th International Conference on Exploring Modeling Methods for Systems Analysis and Development, EMMSAD 2023 - Zaragoza, Spain
Duration: 12 Jun 202313 Jun 2023

Publication series

NameLecture Notes in Business Information Processing
Volume479 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Conference

Conference24th International Conference on Business Process Modeling, Development, and Support, BPMDS 2023 and 28th International Conference on Exploring Modeling Methods for Systems Analysis and Development, EMMSAD 2023
Country/TerritorySpain
CityZaragoza
Period12/06/2313/06/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Event abstraction
  • Interleaved data
  • Network traffic
  • Sequence models

ASJC Scopus subject areas

  • Management Information Systems
  • Control and Systems Engineering
  • Business and International Management
  • Information Systems
  • Modeling and Simulation
  • Information Systems and Management

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