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Hands-on cybersecurity training behavior data for process mining.

Radek Ošlejšek1, Martin Macák1, Karolína Dočkalová Burská1

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This summary is machine-generated.

This study introduces new datasets for process mining in cybersecurity training, simplifying the analysis of trainee behavior. These processed event logs facilitate learning analytics in cyber ranges.

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Area of Science:

  • Cybersecurity Education
  • Learning Analytics
  • Process Mining

Background:

  • Cybersecurity training exercises generate valuable behavioral data through event logs.
  • Organizing these exercises and processing raw data for analysis is challenging.
  • Existing methods require data transformation for process mining techniques.

Purpose of the Study:

  • To present two novel datasets derived from cybersecurity training exercises.
  • To facilitate the application of process mining in learning analytics for cybersecurity.
  • To provide readily usable data for analyzing trainee behavior.

Main Methods:

  • Collection of event logs from two distinct cybersecurity training exercises.
  • Processing and transformation of raw behavioral data into a format suitable for process mining.
  • Generation of joint CSV files from training progress events, Bash commands, and Metasploit commands.

Main Results:

  • Two datasets were created from exercises with 52 and 42 participants, respectively.
  • A total of 11,757 events were collected, including training progress, Bash, and Metasploit commands.
  • The processed data is ready for input into existing process mining tools.

Conclusions:

  • The presented datasets simplify the use of process mining for learning analytics in cybersecurity training.
  • These datasets enable more efficient analysis of trainee behavior in cyber ranges.
  • The research addresses the data preparation bottleneck in applying process mining to cybersecurity education.