41 citations · 49 across the 7 of their papers we have counts for
8 papers
Transformers in Protein: A Survey
Xiaowen Ling, Zhiqiang Li, Yanbin Wang +1
As protein informatics advances rapidly, the demand for enhanced predictive accuracy, structural analysis, and functional understanding has intensified. Transformer models, as powe…
Struggle with Adversarial Defense? Try Diffusion
Yujie Li, Yanbin Wang, Haitao Xu +4
Adversarial attacks induce misclassification by introducing subtle perturbations. Recently, diffusion models are applied to the image classifiers to improve adversarial robustness…
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…