Detecting anomaly in big data system logs using convolutional neural network
Nowadays, big data systems are being widely adopted by many domains for offering
effective data solutions, such as manufacturing, healthcare, education, and media. Big data …
effective data solutions, such as manufacturing, healthcare, education, and media. Big data …
Logbert: Log anomaly detection via bert
Detecting anomalous events in online computer systems is crucial to protect the systems
from malicious attacks or malfunctions. System logs, which record detailed information of …
from malicious attacks or malfunctions. System logs, which record detailed information of …
Experience report: Deep learning-based system log analysis for anomaly detection
Logs have been an imperative resource to ensure the reliability and continuity of many
software systems, especially large-scale distributed systems. They faithfully record runtime …
software systems, especially large-scale distributed systems. They faithfully record runtime …
Anomaly detection of system logs based on natural language processing and deep learning
M Wang, L Xu, L Guo - 2018 4th International Conference on …, 2018 - ieeexplore.ieee.org
System logs record the execution trajectory of the system and exist in all components of the
system. Nowadays, the systems are deployed in a distributed environment and they …
system. Nowadays, the systems are deployed in a distributed environment and they …
Deeplog: Anomaly detection and diagnosis from system logs through deep learning
Anomaly detection is a critical step towards building a secure and trustworthy system. The
primary purpose of a system log is to record system states and significant events at various …
primary purpose of a system log is to record system states and significant events at various …
Logtransfer: Cross-system log anomaly detection for software systems with transfer learning
R Chen, S Zhang, D Li, Y Zhang, F Guo… - 2020 IEEE 31st …, 2020 - ieeexplore.ieee.org
System logs, which describe a variety of events of software systems, are becoming
increasingly popular for anomaly detection. However, for a large software system, current …
increasingly popular for anomaly detection. However, for a large software system, current …
Log-based anomaly detection with deep learning: How far are we?
Software-intensive systems produce logs for troubleshooting purposes. Recently, many
deep learning models have been proposed to automatically detect system anomalies based …
deep learning models have been proposed to automatically detect system anomalies based …
Swisslog: Robust and unified deep learning based log anomaly detection for diverse faults
Log-based anomaly detection has been widely studied and achieves a satisfying
performance on stable log data. But, the existing approaches still fall short meeting these …
performance on stable log data. But, the existing approaches still fall short meeting these …
LogUAD: Log unsupervised anomaly detection based on Word2Vec
J Wang, C Zhao, S He, Y Gu, O Alfarraj… - Computer Systems …, 2022 - zuscholars.zu.ac.ae
Abstract System logs record detailed information about system operation and are important
for analyzing the system's operational status and performance. Rapid and accurate …
for analyzing the system's operational status and performance. Rapid and accurate …
Self-attentive classification-based anomaly detection in unstructured logs
The detection of anomalies is an essential data mining task for achieving security and
reliability in computer systems. Logs are a common and major data source for anomaly …
reliability in computer systems. Logs are a common and major data source for anomaly …