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From Incomplete Architecture to Quantified Risk: Multimodal LLM-Driven Security Assessment for Cyber-Physical Systems

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学术前沿 6.0 分 — 有一定参考价值的AI研究论文
原文: cs.AI updates on arXiv.org

评分 6.0 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-08

评分依据:有一定参考价值的AI研究论文

arXiv:2604.05674v1 Announce Type: cross Abstract: Cyber-physical systems often contend with incomplete architectural documentation or outdated information resulting from legacy technologies, knowledge management gaps, and the complexity of integrating diverse subsystems over extended operational lifecycles. This architectural incompleteness impedes reliable security assessment, as inaccurate or missing architectural knowledge limits the identification of system dependencies, attack surfaces, and risk propagation pathways. To address this foundational challenge, this paper introduces ASTRAL (Ar


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