collaborators

10 papers

cs.CR2026

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…

cs.CR2025

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…

cs.CR2025

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…

cs.CR2025

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…

cs.CR2025

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:…

cs.CR2025

Breaking Obfuscation: Cluster-Aware Graph with LLM-Aided Recovery for Malicious JavaScript Detection

Zhihong Liang, Xin Wang, Zhenhuang Hu +5

With the rapid expansion of web-based applications and cloud services, malicious JavaScript code continues to pose significant threats to user privacy, system integrity, and enterp…