Semi-Supervised Malware Clustering Based on the Weight of Bytecode and API
With the rapid advances of anti-virus and anti-tracking technologies, three aspects in malware clustering need to be improved for effective clustering, i.e., the robustness of features, the accuracy of similarity measurements, and the effectiveness of clustering algorithms. In this paper, we propose...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8943285/ |