Multiple-index network traffic data indexing method, device and storage medium

Abstract

The invention relates to the technical field of network traffic data analysis, aiming at the problems existing in the prior art, the invention provides a multi-index network traffic data index method,a device and a storage medium. At first, the network flow data is analyzed and the data packet index information is extracted; then, session reorganization is carried out. The significance of session reorganization is that it can merge a large amount of redundant data packets and reduce the volume of session index. Finally, session index information is established for all sessions. The session index consists of a session common header and packet index information, and can be used to quickly locate all the packet index information of the session through the session index. The packet index iscomposed of a packet length, an offset position in the file and a file number, which can accurately read the original network traffic data through the file number, offset position and packet length inthe packet index.

Description

technical field [0001] The invention relates to the technical field of network traffic data analysis, in particular to a multi-index network traffic data indexing method, device and storage medium. Background technique [0002] With the development of network technology and the popularization of various network business applications, the network has become an indispensable information carrying tool in people's daily work and life. Through the analysis of network traffic data, it can help network technicians better understand network operation and network traffic content, better maintain and optimize the network, improve communication performance and security, and improve the efficiency of problem solving. The explosive growth of network traffic data has brought great challenges for network technicians to analyze data. The existing mainstream network traffic data analysis tools have many shortcomings, such as: slow file loading speed, high hardware resource usage, and each qu...

AI Technical Summary

Problems solved by technology

The explosive growth of network traffic data has brought great challenges for network technicians to analyze data. The existing mainstream network traffic data analysis tools have many shortcomings, such as: slow file loading speed, high hardware resource usage, and each query requires Search the entire file, the response speed is slow, only one file can be analyzed at a time, and multiple files cannot be analyzed at the same time, etc.

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