41 citations · 46 across the 6 of their papers we have counts for
6 papers · 1 filter
Minos: A Multi-Agent Collaborative Framework for Provenance-Based Backward Tracking
Jiahui Wang, Zhenyuan Li, Zhengkai Wang +2
Sophisticated cyber attacks, particularly Advanced Persistent Threats (APTs), require effective post-intrusion forensic analysis. Provenance-based backward tracking reconstructs at…
Vul-LMGNNs: Fusing language models and online-distilled graph neural networks for code vulnerability detection
Ruitong Liu, Yanbin Wang, Haitao Xu +4
Code Language Models (codeLMs) and Graph Neural Networks (GNNs) are widely used in code vulnerability detection. However, GNNs often rely on aggregating information from adjacent n…
Marlin: Knowledge-Driven Analysis of Provenance Graphs for Efficient and Robust Detection of Cyber Attacks
Zhenyuan Li, Yangyang Wei, Xiangmin Shen +9
Recent research in both academia and industry has validated the effectiveness of provenance graph-based detection for advanced cyber attack detection and investigation. However, an…
Fed-urlBERT: Client-side Lightweight Federated Transformers for URL Threat Analysis
Yujie Li, Yanbin Wang, Haitao Xu +4
In evolving cyber landscapes, the detection of malicious URLs calls for cooperation and knowledge sharing across domains. However, collaboration is often hindered by concerns over…
TransURL: Improving malicious URL detection with multi-layer Transformer encoding and multi-scale pyramid features
Ruitong Liu, Yanbin Wang, Zhenhao Guo +4
Machine learning progress is advancing the detection of malicious URLs. However, advanced Transformers applied to URLs face difficulties in extracting local information, character-…
PMANet: Malicious URL detection via post-trained language model guided multi-level feature attention network
Ruitong Liu, Yanbin Wang, Haitao Xu +4
The proliferation of malicious URLs has made their detection crucial for enhancing network security. While pre-trained language models offer promise, existing methods struggle with…