Malware Family Detection
2 papers with code • 1 benchmarks • 2 datasets
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Benchmarks
These leaderboards are used to track progress in Malware Family Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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MalNet
Malimg
Most implemented papers
Data Augmentation Based Malware Detection using Convolutional Neural Networks
The main contributions of the paper's model structure consist of three components, including image generation from malware samples, image augmentation, and the last one is classifying the malware families by using a convolutional neural network model.
Self-Supervised Vision Transformers for Malware Detection
Malware detection plays a crucial role in cyber-security with the increase in malware growth and advancements in cyber-attacks.
