Malware recognition approach based on self‐similarity and an improved clustering algorithm
Abstract The recognition of malware in network traffic is an important research problem. However, existing solutions addressing this problem rely heavily on the source code and misrecognise vulnerabilities (i.e. incur a high false positive rate (FPR)) in some cases. In this paper, we initially use t...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-10-01
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| Series: | IET Software |
| Online Access: | https://doi.org/10.1049/sfw2.12067 |
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