metadata
license: mit
library_name: sklearn
tags:
- malware-detection
- ember
- cybersecurity
- random-forest
- pe-files
- security
EMBER Malware Random Forest
A Random Forest classifier trained on the EMBER (Elastic Malware Benchmark for Empowering Researchers) dataset for PE malware detection.
Model Details
- Model Type: Random Forest Classifier
- Framework: scikit-learn
- Dataset: EMBER v2 (1M+ PE samples)
- Input: 2381-dimension feature vector
- Output: Malicious / Benign classification
Performance
Trained on the standard EMBER training split with optimized hyperparameters.
| Metric | Score |
|---|---|
| AUC-ROC | ~0.99 |
| Accuracy | ~97% |
| F1 Score | ~0.96 |
Related
- malware-detector-rf - Production variant
- malware-detector-demo - Interactive demo