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https://github.com/trykatchup/ml-iot-malware-analysis

Machine Learning models for IoT traffic malware detection. (Cybersecurity - Alma Mater Studiorum - University of Bologna)
https://github.com/trykatchup/ml-iot-malware-analysis

automl automl-experiments cybersecurity iot iot23 machine-learning random-forest svm

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Machine Learning models for IoT traffic malware detection. (Cybersecurity - Alma Mater Studiorum - University of Bologna)

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# ML-IOT-malware-analysis
Machine Learning models for IoT traffic malware detection. (Cybersecurity - Alma Mater Studiorum - University of Bologna)

## Contents
- [IoT23_preprocessing.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/IoT23_preprocessing.ipynb): Jupyter Notebook with preprocessing operations, useful for both [tabular_prediction_AutoGluon.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/autogluon/tabular_prediction_AutoGluon.ipynb) and [training_ML_models.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/ml-classic/training_ML_models.ipynb).

- [tabular_prediction_AutoGluon.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/autogluon/tabular_prediction_AutoGluon.ipynb): Jupyter Notebook with AutoGluon Tabular experiments.

- [training_ML_models.ipynb](https://github.com/TryKatChup/ML-IOT-malware-analysis/blob/main/ml-classic/training_ML_models.ipynb): Jupyter Notebook with classic Machine Learning Model training (random forest, SVM linear and with rbf kernel).

- [reports](https://github.com/TryKatChup/ML-IOT-malware-analysis/tree/main/reports): my reports.