Abstract The large-scale deployment of IoT devices has led to widespread use of stripped firmware binaries, where function names are removed, leaving many functions anonymous. This obscures program semantics and heightens security risks by hiding vulnerabilities. Recovering meaningful function names is thus crucial for reverse engineering and security analysis. Existing approaches treat naming as an isolated prediction task or rely on static, limited calling contexts, struggling with deep call chains and severe semantic loss. To overcome this, we propose SemFlow , a call-graph-driven, hierarchical semantic propagation method. SemFlow reframes naming as an iterative process that progressively resolves anonymity by leveraging the call graph’s structure: it first recovers bottom-layer functions with richer context and propagates their names upward as semantic anchors to enrich context for mid- and top-layer functions. We evaluate SemFlow on real-world binaries across four architectures (x86-64, x86-32, ARM, MIPS) and four optimization levels (O0–O3). Results show consistent superiority over the state-of-the
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