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Yanxia Sun

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Open access Aug 2026

Reliability auditing of explanations for machine-learning-based intrusion detection systems

Among the high-performing models, XGBoost provided the strongest balance on IoT-ToN, while Random Forest provided the strongest balance on UNSW-NB15, and the reliability results show that high predictive performance does not automatically imply trustworthy explanations.

Elijah M. Maseno, Yan-Xia Sun, Zeng-Hui Wang · 0 citations
Open access Jul 2026

Detecting adversarial evasion in deep learning intrusion detection systems using explainable AI

Deep learning based network intrusion detection systems (IDS) can achieve strong traffic classification performance, but their resilience to adversarial manipulation remains a critical concern. This study evaluates the adversarial robustness of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models in a mu...

Elijah M. Maseno, Yanxia Sun, Zenghui Wang · 0 citations

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