A neuro-symbolic framework reconstructs semantics from opaque binaries via abstract interpretation, reflexive LLM prompting, typed knowledge graphs, and Graphormer reasoning to outperform baselines in vulnerability detection and APT matching for industrial control systems.
IEEE Transactions on Dependable and Secure Computing , volume=
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Securing the Dark Matter: A Semantic-Enhanced Neuro-Symbolic Framework for Supply Chain Analysis of Opaque Industrial Software
A neuro-symbolic framework reconstructs semantics from opaque binaries via abstract interpretation, reflexive LLM prompting, typed knowledge graphs, and Graphormer reasoning to outperform baselines in vulnerability detection and APT matching for industrial control systems.