LDAM: A lightweight dual attention module for optimizing automotive malware classification
In recent years, electric vehicles have become prime targets for cyberattacks, with attackers exploiting public charging stations, USB ports, and other entry points to implant malware. This can lead to network outages and power disruptions. Traditional rule-based classification methods struggle agai...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Array |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590005625000232 |
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