Research on System Log Analysis Based on Bidirectional LSTM

Abstract

System logs often record important information in the system and are an important source of information on user behavior, system abnormalities, and system operating conditions. With the stacking of system time and the surge of users, the data generated by the system has also exploded. In order to achieve intelligent system management, this paper proposes a system log analysis method based on bidirectional LSTM. The method uses neural networks to extract keywords and data vectors based on the logs generated by the system, and uses the data sequence corresponding to the keywords as input to make judgments about system abnormalities. The experimental results show that the method can effectively judge the abnormality of the system.