Ensemble models like Random Forest and Gradient Boosting maintain more stable performance than Logistic Regression and Deep Neural Networks under label manipulation and outlier-based poisoning attacks on IoT intrusion detection datasets.
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Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks
Ensemble models like Random Forest and Gradient Boosting maintain more stable performance than Logistic Regression and Deep Neural Networks under label manipulation and outlier-based poisoning attacks on IoT intrusion detection datasets.