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English(EN) GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks

GenTI基准测试使用LLM自动生成IDPS规则

研究人员开发了GenTI,这是一个新的基准测试和框架,旨在评估大型语言模型(LLM)自动生成入侵检测和防御系统(IDPS)规则的能力。该系统旨在解决手动创建规则的局限性,这些规则难以应对新威胁。GenTI包含一个包含超过150,000条规则的大型数据集,以及一个使用LLM通过结构化提示和验证循环来创建可部署规则的管道。 AI

影响 为LLM在网络安全领域的应用建立了一个新的基准,有可能改进自动威胁检测和响应。

排序理由 该集群包含一篇研究论文,详细介绍了用于评估LLM在特定网络安全任务中的新基准和方法。 [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

GenTI基准测试使用LLM自动生成IDPS规则

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该集群包含一篇研究论文,详细介绍了用于评估LLM在特定网络安全任务中的新基准和方法。 [lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hassan Jalil Hadi, Rehana Yasmin, Ali Shoker ·

    GenTI:为看不见的攻击生成自主IDPS规则的LLM基准测试

    arXiv:2606.05844v1 Announce Type: cross Abstract: Rule-based Intrusion Detection and Prevention Systems (IDPS) offer precise attack detection as well as mitigation, however their manually crafted, signature-driven rules limit adaptability to emerging and zero-day threats. Additio…