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Conceptual Model of Visual Analytics for Hands-on Cybersecurity Training.

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    This summary is machine-generated.

    Visual analytics enhance cybersecurity training by supporting skill development and sensemaking. This approach provides a framework for designing effective training tools and evaluating program success.

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    Area of Science:

    • Cybersecurity Education
    • Information Visualization
    • Human-Computer Interaction

    Background:

    • Hands-on training is crucial for developing practical cybersecurity skills.
    • Existing training methods may not fully leverage data visualization for skill enhancement.
    • Effective training design requires robust methods for sensemaking and evaluation.

    Purpose of the Study:

    • To apply visual analytics principles to the design, execution, and evaluation of cybersecurity training.
    • To propose a conceptual model that integrates visual analytics into the training lifecycle.
    • To provide a framework for developing new visualization tools for cybersecurity training.

    Main Methods:

    • Developing a conceptual model based on extensive experience in cybersecurity training.
    • Classifying visualizations relevant to different phases of the training lifecycle.
    • Applying the model to practical examples from cybersecurity training programs.

    Main Results:

    • A conceptual model integrating visual analytics into cybersecurity training was developed.
    • The model offers a classification of visualizations to support training activities.
    • Demonstrated applicability across different types of cybersecurity training programs.

    Conclusions:

    • Visual analytics can significantly improve the design and effectiveness of cybersecurity training.
    • The proposed model serves as a foundation for creating advanced visualization tools.
    • This framework aids in enhancing participant skill acquisition and sensemaking during training.