An uncertainty-driven probabilistic framework for modeling worm propagation in large-scale networks. It uses stochastic infection rates to capture bursty behavior, adaptive slowdowns, and defense mechanisms, improving prediction accuracy over traditional models while remaining safe, reproducible, and suitable for cybersecurity research.
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Updated
Apr 7, 2026 - Jupyter Notebook