English(EN) Towards Hierarchical Cyber Defense with Large Language Models: From Planning to Execution

LLM 在无需再训练的分层网络防御中展现潜力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-02 04:00

研究人员探索了大型语言模型（LLM）在分层网络防御系统中的应用。通过将 LLM 集成到网络防御的规划和执行阶段，他们发现足够强大的冻结 LLM 可以在各种网络规模下保持强大的防御性能，而无需进行特定任务的再训练。这种方法，特别是当 LLM 控制扩展到战术执行时，与通常需要针对不同网络规模进行再训练的传统强化学习基线相比，显示出显著的改进。 AI

影响 LLM 有可能减少跨不同网络规模的网络防御系统再训练的需求，提高效率和适应性。

排序理由介绍 LLM 在网络防御中新应用的论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Harshith Doppalapudi, Nathaniel D. Bastian, Ankit Shah · 2026-10-02 04:00

利用大型语言模型实现分层网络防御：从规划到执行

arXiv:2610.00590v1 Announce Type: cross Abstract: An autonomous cyber defender trained with reinforcement learning (RL) is typically tied to the network on which it was trained, limiting its ability to generalize as network scale changes. Hierarchical RL reduces decision complexi…

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利用大型语言模型实现分层网络防御：从规划到执行

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