5 papers
An Automated Attack Investigation Approach Leveraging Threat-Knowledge-Augmented Large Language Models
Rujie Dai, Peizhuo Lv, Yujiang Gui +7
Advanced Persistent Threats (APTs) are prolonged, stealthy intrusions by skilled adversaries that compromise high-value systems to steal data or disrupt operations. Reconstructing…
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…
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…
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…
ASGNet: Adaptive Semantic Gate Networks for Log-Based Anomaly Diagnosis
Haitian Yang, Degang Sun, Wen Liu +3
Logs are widely used in the development and maintenance of software systems. Logs can help engineers understand the runtime behavior of systems and diagnose system failures. For an…