41 citations · 44 across the 12 of their papers we have counts for
12 papers
IP-Augmented Multi-Modal Malicious URL Detection Via Token-Contrastive Representation Enhancement and Multi-Granularity Fusion
Ye Tian, Yanqiu Yu, Liangliang Song +3
Malicious URL detection remains a critical cybersecurity challenge as adversaries increasingly employ sophisticated evasion techniques including obfuscation, character-level pertur…
URL2Graph++: Unified Semantic-Structural-Character Learning for Malicious URL Detection
Ye Tian, Yifan Jia, Yanbin Wang +3
Malicious URL detection remains a major challenge in cybersecurity, primarily due to two factors: (1) the exponential growth of the Internet has led to an immense diversity of URLs…
LMAE4Eth: Generalizable and Robust Ethereum Fraud Detection by Exploring Transaction Semantics and Masked Graph Embedding
Yifan Jia, Yanbin Wang, Jianguo Sun +2
Current Ethereum fraud detection methods rely on context-independent, numerical transaction sequences, failing to capture semantic of account transactions. Furthermore, the pervasi…
KGBERT4Eth: A Feature-Complete Transformer Powered by Knowledge Graph for Multi-Task Ethereum Fraud Detection
Yifan Jia, Ye Tian, Liguo Zhang +3
Ethereum's rapid ecosystem expansion and transaction anonymity have triggered a surge in malicious activity. Detection mechanisms currently bifurcate into three technical strands:…
Bridging Source Code and Bytecode for Smart Contract Vulnerability Detection via Dual-Perspective Cross-Modal Distillation
Ye Tian, Yifan Jia, Yanbin Wang +4
Smart contract vulnerabilities have caused substantial financial losses, yet most deployed contracts are closed-source, forcing detection to operate on bytecode --- which lacks the…
DiT-SGCR: Directed Temporal Structural Representation with Global-Cluster Awareness for Ethereum Malicious Account Detection
Ye Tian, Liangliang Song, Peng Qian +3
The detection of malicious accounts on Ethereum - the preeminent DeFi platform - is critical for protecting digital assets and maintaining trust in decentralized finance. Recent ad…
WebGuard++:Interpretable Malicious URL Detection via Bidirectional Fusion of HTML Subgraphs and Multi-Scale Convolutional BERT
Ye Tian, Zhang Yumin, Yifan Jia +2
URL+HTML feature fusion shows promise for robust malicious URL detection, since attacker artifacts persist in DOM structures. However, prior work suffers from four critical shortco…
From Past to Present: A Survey of Malicious URL Detection Techniques, Datasets and Code Repositories
Ye Tian, Yanqiu Yu, Jianguo Sun +1
Malicious URLs persistently threaten the cybersecurity ecosystem, by either deceiving users into divulging private data or distributing harmful payloads to infiltrate host systems.…
The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Survey
Tianxu Liu, Yanbin Wang, Jianguo Sun +5
As blockchain technology rapidly evolves, the demand for enhanced efficiency, security, and scalability grows.Transformer models, as powerful deep learning architectures,have shown…
Ethereum Fraud Detection via Joint Transaction Language Model and Graph Representation Learning
Jianguo Sun, Yifan Jia, Yanbin Wang +3
Ethereum faces growing fraud threats. Current fraud detection methods, whether employing graph neural networks or sequence models, fail to consider the semantic information and sim…
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…