System-log classification method

Abstract

The invention provides a method of extracting a feature vector from a system log, a method of constructing a system-log classification model and a system-log classification method. The method of extracting the feature vector includes: for each category, calculating semantic similarity degrees of keywords of the category and the system log, and selecting certain similarity degrees to use the same as a feature vector of the system log under the category; and combining the feature vectors of the system log under all the categories to obtain the feature vector of the system log. According to the method of constructing the model, the method of extracting the feature vector is utilized to extract feature vectors of a training data set, and the same are used as input of a convolutional neural network (CNN) to train the model. According to the system-log classification method, the method of extracting the feature vector is utilized to extract a feature vector of a system log, and a classification result is obtained through the model. The methods can realize system-log classification of high accuracy and high timeliness.

Description

technical field [0001] The invention relates to the field of log processing and analysis, in particular to system log classification technology. Background technique [0002] System logs are used to record hardware, software, and system problems in computer systems, and to monitor events that occur in the system. System logs in a broad sense include system RAS logs and system security audit logs, etc. Administrators can check the system status at any time by viewing system logs, check the cause of errors, or look for traces left by attackers when they are attacked. [0003] When the number of system logs is increasing day by day, it is necessary to sort out different types of system logs. By classifying system logs, system administrators can continuously observe the health status of the system, locate root faults, and perform task scheduling and performance optimization. Existing system log classification methods include density-based methods, cluster analysis-based method...

AI Technical Summary

Problems solved by technology

However, the accuracy and time efficiency of these classification methods are generally not high, especially when classifying system logs of large data sets, these methods have a significant decline in classification accuracy and time efficiency

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