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cs.CR2025
Mitigating the Impact of Malware Evolution on API Sequence-based Windows Malware Detector
Xingyuan Wei, Ce Li, Qiujian Lv +3
In dynamic Windows malware detection, deep learning models are extensively deployed to analyze API sequences. Methods based on API sequences play a crucial role in malware preventi…
cs.CR2025
DWFS-Obfuscation: Dynamic Weighted Feature Selection for Robust Malware Familial Classification under Obfuscation
Xingyuan Wei, Zijun Cheng, Ning Li +3
Due to its open-source nature, the Android operating system has consistently been a primary target for attackers. Learning-based methods have made significant progress in the field…
cs.CR2024
PromptSAM+: Malware Detection based on Prompt Segment Anything Model
Xingyuan Wei, Yichen Liu, Ce Li +3
Machine learning and deep learning (ML/DL) have been extensively applied in malware detection, and some existing methods demonstrate robust performance. However, several issues per…