Malware Detection using Machine Learning techniques by Umer Nazeer

Malware Detection using Machine Learning techniques

Umer Nazeer

Data Scientist

ML Engineer

AI Model Developer

pandas

Python

scikit-learn

IoT-based and malware-based attacks are increasingly targeting Critical Infrastructure

The malware_project.ipynb file contains the analysis performed on the MalMem2022 dataset.

The creating-a-smaller-dataset-for-ciciot2023.ipynb is primarily built to reduce the size of the CICIot2023 dataset which is 13 GBs in size.

This could be helpful in performing analysis on the dataset for example Feature Engineering, Variance and Corelation analysis, Feature Selection etc.

The iot_project.ipynb file contains analysis performed on the CICIot2023 dataset, the feature engineering has been performed a simpler subset of the CICIot2023 dataset.

The notebooks assume that the Obfuscated-MalMem2022.csv file and the CICIoT2023 directory as extacted from the zip format containing all the parts of the complete CICIoT2023 dataset are both present in the working directory of this project.

If this is not the case, please specify the paths to these files.

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