Comparative analysis on imbalanced multi-class classification for malware samples using CNN
Malware considered as one of the main actors in cyber attacks. Everyday, the number of unique malware samples are in the rise, however the ratio of benign software still greatly outnumbers malware samples. In machine learning, such datasets are known as imbalanced, where the majority class label gre...
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| Main Authors: | , , , , |
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| Format: | Default Conference proceeding |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/10007939.v1 |
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