Integrating Graph Theoretical Approaches in Cybersecurity Education CSCI-RTED

• URL: http://arxiv.org/abs/2504.17059v1
• Date: Wed, 23 Apr 2025 19:08:30 GMT
• Title: Integrating Graph Theoretical Approaches in Cybersecurity Education CSCI-RTED
• Authors: Goksel Kucukkaya, Murat Ozer, Kazim Ciris,
• Abstract summary: Graph theory offers a powerful framework for modeling relationships within cyber ecosystems.<n>This paper develops an enriched version of the widely recognized NSL-KDD dataset, incorporating graph-theoretical concepts to enhance its practical value.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As cybersecurity threats continue to evolve, the need for advanced tools to analyze and understand complex cyber environments has become increasingly critical. Graph theory offers a powerful framework for modeling relationships within cyber ecosystems, making it highly applicable to cybersecurity. This paper focuses on the development of an enriched version of the widely recognized NSL-KDD dataset, incorporating graph-theoretical concepts to enhance its practical value. The enriched dataset provides a resource for students and professionals to engage in hands-on analysis, enabling them to explore graph-based methodologies for identifying network behavior and vulnerabilities. To validate the effectiveness of this dataset, we employed IBM Auto AI, demonstrating its capability in real-world applications such as classification and threat prediction. By addressing the need for graph-theoretical datasets, this study provides a practical tool for equipping future cybersecurity professionals with the skills necessary to confront complex cyber challenges.

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