The paper demonstrates that multicollinearity inflates explanation variance in AI models for intrusion detection and introduces a fragility metric plus two mitigation techniques to stabilize attributions.
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Stabilising Explainability Fragility in Cybersecurity AI: The Impact and Mitigation of Multicollinearity in Public Benchmark Datasets
The paper demonstrates that multicollinearity inflates explanation variance in AI models for intrusion detection and introduces a fragility metric plus two mitigation techniques to stabilize attributions.