{
  "added_at": "2026-11-06",
  "arxiv_id": "2403.18403",
  "arxiv_version_reviewed": "v3",
  "authors": [
    "Xiuwei Shang",
    "Guoqiang Chen",
    "Shaoyin Cheng",
    "Shikai Guo",
    "Yanming Zhang",
    "Weiming Zhang",
    "Nenghai Yu"
  ],
  "bibtex_url": "https://awesomerea.org/papers/citations/paper-foc.bib",
  "code_url": null,
  "date_basis": "First arXiv submission date.",
  "date_basis_zh": "arXiv 首次提交日期。",
  "date_precision": "day",
  "description_en": "FoC uses FoC-BinLLM to summarize cryptographic functions in stripped binaries and FoC-Sim to retrieve similar implementations. It evaluates both models and applications to virus analysis and 1-day vulnerability detection.",
  "description_zh": "FoC 使用 FoC-BinLLM 概括去符号二进制文件中密码函数的语义，并使用 FoC-Sim 检索相似实现。论文评估了两个模型，以及它们在病毒分析和已披露一天的漏洞检测中的应用。",
  "doi": null,
  "entry_url": "https://awesomerea.org/papers/paper-foc/",
  "entry_url_zh": "https://awesomerea.org/zh/papers/paper-foc/",
  "evidence_urls": [
    "https://arxiv.org/abs/2403.18403"
  ],
  "first_arxiv_date": "2024-03-27",
  "id": "paper-foc",
  "json_url": "https://awesomerea.org/papers/paper-foc/record.json",
  "kind": "research",
  "markdown_url": "https://awesomerea.org/papers/paper-foc/index.md",
  "markdown_url_zh": "https://awesomerea.org/zh/papers/paper-foc/index.md",
  "metadata_notes": "The date and venue come from the arXiv record.",
  "metadata_notes_zh": "日期和发表场所来自 arXiv 记录。",
  "pdf_url": "https://arxiv.org/pdf/2403.18403",
  "project_url": null,
  "publication_date": "2024-03-27",
  "publication_status": "preprint",
  "record_type": "paper",
  "runtime_tested": false,
  "scope_limitations_en": "Evaluation uses a constructed cryptographic binary dataset and automatically generated semantic labels. It reports a 14.61% higher ROUGE-L score than ChatGPT for FoC-BinLLM and 52% higher Recall@1 than previous best methods for FoC-Sim.",
  "scope_limitations_zh": "评估使用构建的密码函数二进制数据集和自动生成的语义标签。论文报告 FoC-BinLLM 的 ROUGE-L 分数比 ChatGPT 高 14.61%，FoC-Sim 的 Recall@1 比此前最佳方法高 52%。",
  "targets": [
    "binary"
  ],
  "title": "FoC: Figure out the Cryptographic Functions in Stripped Binaries with LLMs",
  "title_zh": "FoC：利用大语言模型识别去符号二进制文件中的密码函数",
  "url": "https://arxiv.org/abs/2403.18403",
  "venue": "arXiv",
  "verification": "source-reviewed",
  "verified_at": "2026-11-06",
  "why_fits_en": "It addresses reverse engineering of cryptographic functions in stripped binaries through semantic analysis and similarity retrieval.",
  "why_fits_zh": "论文通过语义分析和相似实现检索，研究去符号二进制文件中密码函数的逆向分析。",
  "year": 2024
}