Android malware detection method based on highly distinguishable static features and DenseNet
The rapid growth of malware has become a serious problem that threatens the security of the mobile ecosystem and needs to be studied and resolved. Android is the main target of attackers due to its open source and popularity. To solve this serious problem, an accurate and efficient malware detection...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9683612/?tool=EBI |