Kwame Agyeman-Prempeh Agyekum
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Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks
This paper analyzes how vulnerable various machine learning models are to data poisoning attacks in IoT intrusion detection, finding that ensemble methods are more robust than Logistic Regression and Deep Neural Networks.
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cs.CRcs.AIRecentApr 15, 2026
Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks
Fortunatus Aabangbio Wulnye, Justice Owusu Agyemang, Kwame Opuni-Boachie Obour Agyekum, Kwame Agyeman-Prempeh Agyekum +2 more
This paper analyzes how vulnerable various machine learning models are to data poisoning attacks in IoT intrusion detection, finding that ensemble methods are more robust than Logistic Regression and…
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