On Graph Theory vs Time-Domain Discrete Event Simulation for Topology-Informed Assessment of Power Grid Cyber Risk
<|reference_start|>On Graph Theory vs Time-Domain Discrete Event Simulation for Topology-Informed Assessment of Power Grid Cyber Risk: The shift toward more renewable energy sources and distributed generation in smart grids has underscored the significance of modeling and analyzing modern power systems as cyber-physical systems (CPS). This transformation has highlighted the importance of cyber and cyber-physical properties of modern power systems for their reliable operation. Graph theory emerges as a pivotal tool for understanding the complex interactions within these systems, providing a framework for representation and analysis. The challenge is vetting these graph theoretic methods and other estimates of system behavior from mathematical models against reality. High-fidelity emulation and/or simulation can help answer this question, but the comparisons have been understudied. This paper employs graph-theoretic metrics to assess node risk and criticality in three distinct case studies, using a Python-based discrete-event simulation called SimPy. Results for each case study show that combining graph theory and simulation provides a topology-informed security assessment. These tools allow us to identify critical network nodes and evaluate their performance and reliability under a cyber threat such as denial of service threats.<|reference_end|>
@article{haque2024on,
    title={On Graph Theory vs. Time-Domain Discrete Event Simulation for
  Topology-Informed Assessment of Power Grid Cyber Risk},
    author={Khandaker Akramul Haque, Leen Al Homoud, Xin Zhuang, Mariam Elnour,
  Ana Goulart and Katherine Davis},
    journal={arXiv preprint arXiv:2409.04590},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.04590},
    primaryClass={math.NA cs.NA}
}