ORIGINAL RESEARCH article
Front. Complex Syst.
Sec. Complex Networks
Volume 3 - 2025 | doi: 10.3389/fcpxs.2025.1620260
Network Modelling in Analysing Cyber-related Graphs
Provisionally accepted
- Aalto University, Otakaari, Finland
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To improve the resilience of the computer network infrastructure against cyber attacks or causal influences and find ways to mitigate their impact, we need to understand their structure and dynamics. Here, we propose a novel network-based influence-spreading modelling approach to investigate event trajectories or paths in attack and causal graphs with directed, weighted, cyclic and/or acyclic paths. In our model, we can perform probabilistic analyses that extend beyond traditional methods to visualise cyber-related graphs. The model uses a probabilistic method to combine paths that join within the graph. This analysis includes vulnerabilities, services, and exploitabilities. To demonstrate the applicability of our model, we present three cyber-related use cases: two attack graphs and one causal graph. This model can serve cyber analysts as a tool to produce quantitative metrics for prioritising tasks, summarising statistics, or analysing large-scale graphs.
Keywords: Attack modelling technique, network modelling, attack graph, Causal graph, Directed acyclic graph
Received: 29 Apr 2025; Accepted: 26 Aug 2025.
Copyright: © 2025 Kuikka, Pykälä, Takko and Kaski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Vesa Kuikka, Aalto University, Otakaari, Finland
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