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Applying Process Discovery to Cybersecurity Training: An Experience Report

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00125678" target="_blank" >RIV/00216224:14330/22:00125678 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/9799415" target="_blank" >https://ieeexplore.ieee.org/document/9799415</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/EuroSPW55150.2022.00047" target="_blank" >10.1109/EuroSPW55150.2022.00047</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Applying Process Discovery to Cybersecurity Training: An Experience Report

  • Original language description

    Quality improvement of practical cybersecurity training is challenging due to the process-oriented nature of this learning domain. Event logs provide only a sparse preview of trainees' behavior in a form that is difficult to analyze. Process mining has great potential in converting events into behavioral graphs that could provide better cognitive features for understanding users' behavior than the raw data. However, practical usability for learning analytics is affected by many aspects. This paper aims to provide an experience report summarizing key features and obstacles in integrating process discovery into cyber ranges. We describe our lessons learned from applying process mining techniques to data captured in a cyber range, which we have been developing and operating for almost ten years. We discuss lessons learned from the whole workflow that covers data preprocessing, data mapping, and the utilization of process models for the post-training analysis of Capture the Flag games. Tactics addressing scalability are explicitly discussed because scalability has proven to be a challenging task. Interactive data mapping and Capture the Flag specific features are used to address this issue.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)

  • ISBN

    9781665495608

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    394-402

  • Publisher name

    IEEE

  • Place of publication

    Neuveden

  • Event location

    Genoa, Italy

  • Event date

    Jan 1, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000853211100040