English(EN) Network Intrusion Forensic Detection System with Explainable Artificial Intelligence and Digital Chain of Custody

AI取证管道确保入侵检测模型的完整性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 05:00

研究人员开发了MODEXRE，一个旨在确保用于入侵检测的可解释人工智能模型完整性和可验证性的取证管道。该系统扩展了一个先前经过验证的XGBoost分类器，并加入了SHAP可解释性，分为两种模式：用于训练和认证的实验室模式，以及用于案件证据推理的正式模式。MODEXRE采用SHA-256哈希链式证据链，以保证认证模型是应用于案件的确切制品，解决了先前影响模型性能的时间戳泄露和特征覆盖范围不足等问题。该管道通过四个关键设计决策进行了优化，显著提高了分类准确性以及识别特定威胁行为的能力。 AI

影响增强了在关键安全和取证应用中使用的AI系统的信任度和可靠性。

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arXiv cs.LG TIER_1 English(EN) · Jose Luis Vela Alonso, Carmen Pellicer · 2026-11-05 05:00

基于可解释人工智能和数字证据链的网络入侵取证检测系统

arXiv:2611.06173v1 Announce Type: cross Abstract: Deploying an explainable intrusion detection model from a validated laboratory setting into a forensic workflow requires guarantees that benchmarks do not test: that the certified model is the exact artifact applied to a case, tha…

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基于可解释人工智能和数字证据链的网络入侵取证检测系统

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