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Published March 30, 2026 | Version 1.0.0

Dataset From Cybersecurity Tabletop Exercises in the INJECT Platform

  • 1. Masaryk University, Faculty of Informatics
  • 1. ROR icon Carnegie Mellon University
  • 2. Masaryk University, Faculty of Informatics

Description

Repository content:

Dataset from cybersecurity tabletop exercises (TTXs) conducted using the open-source INJECT Exercise Platform. For details, please see:

Attribution (How to cite):

If you use or build upon the materials, please use the BibTeX or full-text citation entry to cite the following paper:

Conrad Borchers, Valdemar Švábenský, Sandesh K. Kafle, Kevin K. Tang, and Jan Vykopal.
Multimodal Analytics of Cybersecurity Crisis Preparation Exercises: What Predicts Success?
In Proceedings of the 27th International Conference on Artificial Intelligence in Education (AIED), 2026.
https://arxiv.org/pdf/2603.28553

@article{Borchers2026multimodal,
    author    = {Borchers, Conrad and \v{S}v\'{a}bensk\'{y}, Valdemar and Kafle, Sandesh K. and Tang, Kevin K. and Vykopal, Jan},
    title     = {{Multimodal Analytics of Cybersecurity Crisis Preparation Exercises: What Predicts Success?}},
    booktitle = {Proceedings of the 27th International Conference on Artificial Intelligence in Education},
    series    = {AIED '26},
    location  = {Seoul, Korea},
  publisher = {Springer},
    month     = {06},
  year      = {2026},
  numpages  = {15}, }

Versioning:

  • v. 1.0.0: Data from 23 teams (76 students) in 5 different TTXs. For details regarding the data context, see the paper "Multimodal Analytics of Cybersecurity Crisis Preparation Exercises: What Predicts Success?".

Contact:

If you notice any issues or breaches of the license terms of this dataset, please contact Valdemar Švábenský using the email address listed in the paper "Multimodal Analytics of Cybersecurity Crisis Preparation Exercises: What Predicts Success?".

Files

INJECT-tabletop-exercise-dataset.zip

Files (1.0 MB)

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md5:68d97ea86ee2c00da5ba2541db8d3174
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Additional details

Funding

Ministry of the Interior
Intelligent Tools for Planning, Conducting, and Evaluating Tabletop Exercises VK01030007

Software

Programming language
YAML , JSON