Flow-based electronic resource network behavior analysis practice

Abstract

In a university environment, analyzing the access patterns of electronic resource is crucial for resource management and optimization. A method based on the classification and aggregation of network flows into long and short flows was proposed. By finely classifying and statistically analyzing traffic, it accurately assessed the usage behaviors of different types of users. First, a statistical analysis of traffic related to electronic resource access was performed on the campus network.Then, traffic data related to accessing Sci-Hub was constructed and analyzed. Finally, based on the statistical analysis of electronic resource access traffic, a method for classifying and aggregating long and short flows was proposed. This method effectively classifies electronic resource access behaviors.

Keywords

• traffic analysis
• encrypted traffic detection
• electronic resource
• security analysis