1 citations · 1 across the 1 of their papers we have counts for
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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…
Continuous Multi-Task Pre-training for Malicious URL Detection and Webpage Classification
Yujie Li, Yiwei Liu, Peiyue Li +2
Malicious URL detection and webpage classification are critical tasks in cybersecurity and information management. In recent years, extensive research has explored using BERT or si…
MuFuzz: Sequence-Aware Mutation and Seed Mask Guidance for Blockchain Smart Contract Fuzzing
Peng Qian, Hanjie Wu, Zeren Du +7
As blockchain smart contracts become more widespread and carry more valuable digital assets, they become an increasingly attractive target for attackers. Over the past few years, s…
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…