Mi-maml: classifying few-shot advanced malware using multi-improved model-agnostic meta-learning
Abstract Malware classification has been successful in utilizing machine learning methods. However, it is limited by the reliance on a large number of high-quality labeled datasets and the issue of overfitting. These limitations hinder the accurate classification of advanced malware with only a few...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-11-01
|
| Series: | Cybersecurity |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42400-024-00314-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|