eurecom-s3 / DecodingMLSecretsOfWindowsMalwareClassification

Decoding the Secrets of Machine Learning in Windows Malware Classification: A Deep Dive into Datasets, Features, and Model Performance

This repository hosts the feature importance scores of the following experiments:

1. Binary detection
1. Static
1. All samples
2. Packed only
3. No packed
2. Dynamic
1. All samples
2. Family classification
1. Static
1. All samples
2. Packed only
3. No packed
2. Dynamic
1. All samples

Citation

If you use any of the contents, please cite it as:

@misc{dambra2023decoding,
      title={Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance}, 
      author={Savino Dambra and Yufei Han and Simone Aonzo and Platon Kotzias and Antonino Vitale and Juan Caballero and Davide Balzarotti and Leyla Bilge},
      year={2023},
      eprint={2307.14657},
      archivePrefix={arXiv},
      primaryClass={cs.CR}
}