Overview of Research

Our research includes Fraud Detection, Network Analysis, Smart Contract and Performance.

In the details page, there is a detailed introduction of our research work in this direction as well as related papers, data and codes.

Fraud Detection

In the blockchain ecosystem, there are many illegal activities, such as Ponzi schemes, hacker attacks, market manipulations and so on, which seriously threaten the development of blockchain technology. We establish identification and early warning models for various illegal behaviors based on blockchain data to promote the safe and orderly development of blockchain technology.

Our research work includes:

Smart Ponzi Scheme Detection

Market Ecosystem Analysis

Network Analysis

Network science is the study of complex networks. It provides theories, techniques and tools that help us understand the structure and evolution of a network. The bitcoin transaction network and ethereum transaction network are prime examples. Its basic building block, the transaction, can be combined to produce complex transfers of value. This is reflected in the topological structure of the transaction network.

Our research work includes:

Network Construction

Network Embedding

Temporal Link Prediction

Blockchain Transaction Network Analysis

Mixing Service Detection

Phishing Scams Detection

Smart Contract

Smart contracts can autonomously perform all or part of the contract-related operations and generate corresponding verifiable evidence to illustrate the effectiveness of performing contract operations. Smart contracts exist on various nodes of the blockchain network in the form of on-chain scripts, and their security and costs have attracted much attention.

Our research work includes:

smart contract vulnerability detection and repair

smart contract decompilation

smart contract recommendation


At present, the performance of the blockchain is poor, and for different blockchain systems, there is a lack of standardized performance monitoring methods that can automatically adapt to different systems and provide detailed real-time performance information. In addition, users want to select reliable blockchain peers in public blockchain systems, and they need to evaluate and predict their reliability.

Our research work includes:

Performance Monitoring

Blockchain QoS