Mathematical analysis based on the Macroscopic Fundamental Diagram proves road transportation networks are fragile, with a skewness indicator for cross-network comparison and simulations showing stochastic reinforcement.
Transportation Research Part C: Emerging Technologies 142, 103759
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An integrated framework using autoencoders, deep reinforcement learning, and LLMs automates risk-based prioritization and contextual analysis of suspicious network traffic within Splunk SOC environments.
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The fragile nature of road transportation networks
Mathematical analysis based on the Macroscopic Fundamental Diagram proves road transportation networks are fragile, with a skewness indicator for cross-network comparison and simulations showing stochastic reinforcement.
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Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage
An integrated framework using autoencoders, deep reinforcement learning, and LLMs automates risk-based prioritization and contextual analysis of suspicious network traffic within Splunk SOC environments.