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The paper proposes a hybrid framework combining reinforcement learning with knowledge graph-augmented neural networks for supply chain cyber-threat decision-making. The RL-Knowledge Graph model achieves 95.27% precision.
Cyber supply chains consist of interconnected systems and network nodes. Attacks on one node can spread across the supply chain, making cyber resilience, threat prediction and proactive cybersecurity essential.