Blockchain Transaction Monitoring and Anomaly Analysis System

With the rapid development of blockchain technology, its applications in finance, supply chain management, the Internet of Things, and other fields have become increasingly widespread. However, the expansion of blockchain networks and the surge in transaction volumes have posed challenges for transaction monitoring and anomaly detection. Traditional outlier detection techniques are often not suitable for distributed, high-dimensional blockchain systems. This work introduces a system for monitoring blockchain transactions and analyzing anomalies. By comprehensively utilizing blockchain intelligent behavior analysis technology and the Apache Flink stream processing framework, the system achieves comprehensive monitoring and anomaly detection of transaction activities within blockchain networks. The system primarily comprises key components such as the design of the blockchain intelligent behavior analysis process, the application of the Apache Flink stream processing framework, and the integration of the Kafka distributed event streaming platform. Finally, the system is deployed and tested in a real-world blockchain network environment, verifying its effectiveness and reliability in transaction monitoring and anomaly detection.