New AI tool automates threat modeling for cyber-physical systems

Researchers have developed SMSI, a novel pipeline that automates threat modeling for cyber-physical systems. This system translates architectural models into actionable security control recommendations by mapping system components to vulnerabilities, then to attack techniques, and finally to NIST 800-53 security controls. Experiments using a healthcare IoT gateway demonstrated that SecureBERT, a fine-tuned language model, performed best in linking vulnerabilities to attack techniques, highlighting the effectiveness of dense embeddings for automated security recommendations. AI

IMPACT Automates security control recommendations for cyber-physical systems, potentially improving efficiency and effectiveness of threat modeling.

RANK_REASON This is a research paper detailing a new automated threat modeling pipeline for cyber-physical systems.

Read on arXiv cs.AI →

• arXiv
• Gemma-4 26B
• MITRE ATT&CK
• NIST 800-53
• SecureBERT+

• paper
• safety

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