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Author

Khalid Alalawi

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Review Open access 2026

Explaining the Black Box: An XAI-Driven Trustworthiness Audit of ML-Based IoT Intrusion Detection Across Attack Categories

Machine learning classifiers for Internet of Things (IoT) intrusion detection routinely report accuracy above 99%, yet this conceals systematic failures on operationally important minority categories such as BruteForce and Web-based attacks, and the global explainability analyses usually applied to these models say not...

Khalid Alalawi · 0 citations
Open access 2026

When Calibrated Detectors Meet New Attacks: Per-Category Reliability of Machine-Learning Intrusion Detection Under Distribution Shift

Machine-learning intrusion detectors are usually reported with accuracy or F1 on a single train and test split, and their confidence scores are often read operationally as probabilities without an explicit calibration check. We test that assumption. We measure the reliability of the predicted probabilities of three cla...

Khalid Alalawi · 0 citations

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