Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework | Signal Canvas | ScienceToStartup

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Proof freshness: fresh
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Last proof check: 2026-06-06
Score updated: 2026-06-06
Score fresh until: 2026-07-06
References: 0
Source count: 3
Coverage: 50%

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Canonical ID explainable-ai-driven-cyber-risk-analytics-and-model-reliability-assessment-for-intelligent-governance-of-u-s-critical-i | Route /signal-canvas/explainable-ai-driven-cyber-risk-analytics-and-model-reliability-assessment-for-intelligent-governance-of-u-s-critical-i

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Evidence Receipt

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Claims: 1

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

PDF: https://arxiv.org/pdf/2606.05710v1

Source count: 3

Coverage: 50%

Last proof check: 2026-06-06T03:21:38.659Z

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Subject: Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

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