Abstract Industry 5.0’s increasing integration of IT and OT systems is transforming industrial operations but also expanding the cyber–physical attack surface. Industrial Control Systems (ICS) face escalating security challenges as traditional siloed defenses fail to provide coherent, cross-domain threat insights. We present BRIDG-ICS (BRIDge for Industrial Control Systems), an AI-enriched Knowledge Graph (KG) framework for context-aware threat analysis and quantitative assessment of cyber resilience in smart manufacturing environments. BRIDG-ICS fuses heterogeneous industrial and cybersecurity data into an integrated Industrial Security Knowledge Graph linking assets, vulnerabilities, and adversarial behaviors with probabilistic risk metrics (e.g., exploit likelihood, attack cost). This unified graph representation enables multi-stage attack path simulation using graph-analytic techniques. To enrich the graph’s semantic depth, the framework leverages domain-specific pretrained language models (e.g., SecureBERT, CySecBERT) to extract cybersecurity entities, infer relationships, and transform natural-language threat descriptions into structured graph triples, there
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