Datasets:
Tasks:
Tabular Classification
Formats:
parquet
Languages:
English
Size:
100K - 1M
Tags:
cybersecurity
malware
static-analysis
pe-files
malware-detection
malware-family-classification
Update README.md
Browse files
README.md
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@@ -49,7 +49,7 @@ Please cite the original BODMAS paper when using this cleaned release in researc
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| `bodmas_clean_y.npy` | Label vector (`int32`), `0 = benign`, `1 = malware` |
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| `bodmas_clean_metadata.parquet` | Per-sample metadata: SHA-256, timestamps, family fields, and quality flags |
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| `manifest.json` | Versioned manifest with checksums and artifact references |
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## What’s in the dataset?
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## File structure
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```text
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├── bodmas_clean.npz
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├── bodmas_clean_X.npy
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├── bodmas_clean_y.npy
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To open it locally, run:
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```bash
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jupyter notebook
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```
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or, if you use JupyterLab:
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```bash
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jupyter lab
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```
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Make sure to open the notebook from the dataset root directory so that relative file paths resolve correctly.
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| `bodmas_clean_y.npy` | Label vector (`int32`), `0 = benign`, `1 = malware` |
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| `bodmas_clean_metadata.parquet` | Per-sample metadata: SHA-256, timestamps, family fields, and quality flags |
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| `manifest.json` | Versioned manifest with checksums and artifact references |
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| `bodmas_cleaned_dataset.ipynb` | Exploration and usage notebook |
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## What’s in the dataset?
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## File structure
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```text
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BODMAS_cleaned/
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├── bodmas_clean.npz
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├── bodmas_clean_X.npy
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├── bodmas_clean_y.npy
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To open it locally, run:
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```bash
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jupyter notebook bodmas_cleaned_dataset.ipynb
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```
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or, if you use JupyterLab:
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```bash
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jupyter lab bodmas_cleaned_dataset.ipynb
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```
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Make sure to open the notebook from the dataset root directory so that relative file paths resolve correctly.
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