Machine Learning models for IoT traffic malware detection. (Cybersecurity - Alma Mater Studiorum - University of Bologna)
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Feb 15, 2023 - Jupyter Notebook
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iot23
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Federated learning–based IoT malware detection using the IoT-23 dataset, evaluated under adversarial settings including label flipping, gradient manipulation, sign flipping, and single-client backdoor attacks, with time-aware preprocessing and calibration analysis.
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Jan 8, 2026 - Python
End-to-end federated learning pipeline for IOT-23 network intrusion dataset with self-healing data ingestion and automated schema alignment.
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Jul 9, 2026 - Python
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