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English(EN) XAI-SDN: An Explainable Entropy-Guided Machine Learning Framework for Real-Time DDoS Detection in Software Defined Networks

新AI框架增强软件定义网络中的DDoS检测能力

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了XAI-SDN，一个旨在检测软件定义网络（SDN）中分布式拒绝服务（DDoS）攻击的新机器学习框架。该框架利用香农熵指标和随机森林分类器，并通过SHAP TreeExplainer增强了透明度。XAI-SDN在CIC-DDoS2019基准测试中展示了高准确性，在检测性能上取得了近乎完美的分数，同时保持了高效的处理速度。 AI

影响 该框架为软件定义网络提供了改进的实时DDoS检测和透明度。

排序理由 该项目是一篇研究论文，详细介绍了一个用于网络安全的新机器学习框架。[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 →

新AI框架增强软件定义网络中的DDoS检测能力

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该项目是一篇研究论文，详细介绍了一个用于网络安全的新机器学习框架。[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) · Adeel Ahmad, Ali Akarma, Ahmad Ali, Hammad Muneer, Toqeer Ali Syed ·

    XAI-SDN：面向软件定义网络中实时DDoS检测的可解释熵引导机器学习框架

    arXiv:2609.05701v1 Announce Type: cross Abstract: One of the biggest risks faced by Software Defined Networks (SDN) is the Distributed Denial of Service (DDoS) attack in which a compromised controller can make an entire network unusable. To address these challenges, we suggest an…

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