Research on system log anomaly detection based on deep learning

The system log reflects the running status of the system and records the activity information of specific events in the system.Therefore,the rapid and accurate detection of the system abnormal log is important to the security and stability of the system.A log anomaly detection algorithm based on GRU...

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Bibliographic Details
Main Authors: Yidong WANG, Peishun LIU, Gbin WAN
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2019-10-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019055
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Summary:The system log reflects the running status of the system and records the activity information of specific events in the system.Therefore,the rapid and accurate detection of the system abnormal log is important to the security and stability of the system.A log anomaly detection algorithm based on GRU neural network is proposed.Log parsing is implemented based on log key technology.Log anomaly detection is realized by using anomaly detection model of execution path and anomaly detection model of parameter value.The system has the advantages of less parameters and faster training.It improves the running speed while achieving higher detection accuracy,and is suitable for log analysis of large information systems.
ISSN:2096-109X