A comprehensive survey on applications of AI technologies to failure analysis of industrial systems
Component reliability plays a pivotal role in industrial systems, which are evolving with
larger complexity and higher dimensionality of data. It is insufficient to ensure reliability and …
larger complexity and higher dimensionality of data. It is insufficient to ensure reliability and …
Log‐based anomaly detection for distributed systems: State of the art, industry experience, and open issues
Distributed systems have been widely used in many safety‐critical areas. Any abnormalities
(eg, service interruption or service quality degradation) could lead to application crashes or …
(eg, service interruption or service quality degradation) could lead to application crashes or …
Autolog: A log sequence synthesis framework for anomaly detection
The rapid progress of modern computing systems has led to a growing interest in informative
run-time logs. Various log-based anomaly detection techniques have been proposed to …
run-time logs. Various log-based anomaly detection techniques have been proposed to …
Multivariate Log-based Anomaly Detection for Distributed Database
Distributed databases are fundamental infrastructures of today's large-scale software
systems such as cloud systems. Detecting anomalies in distributed databases is essential …
systems such as cloud systems. Detecting anomalies in distributed databases is essential …
Multi-source log parsing with pre-trained domain classifier
Automated log analysis with AI technologies is commonly used in network, system, and
service operation and maintenance to ensure reliability and quality assurance. Log parsing …
service operation and maintenance to ensure reliability and quality assurance. Log parsing …
AcLog: An Approach to Detecting Anomalies from System Logs with Active Learning
C Duan, T Jia, Y Li, G Huang - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Log-based anomaly detection is an essential aspect of maintaining software reliability,
particularly in the context of microservice systems. However, existing log-based anomaly …
particularly in the context of microservice systems. However, existing log-based anomaly …
Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Study
As software systems grow increasingly intricate, the precise detection of anomalies have
become both essential and challenging. Current log-based anomaly detection methods …
become both essential and challenging. Current log-based anomaly detection methods …
Hilogx: noise-aware log-based anomaly detection with human feedback
T Jia, Y Li, Y Yang, G Huang - The VLDB Journal, 2024 - Springer
Log-based anomaly detection is essential for maintaining system reliability. Although
existing log-based anomaly detection approaches perform well in certain experimental …
existing log-based anomaly detection approaches perform well in certain experimental …
DA-Parser: A Pre-trained Domain-aware Parsing Framework for Heterogeneous Log Analysis
Automated log analysis is widely applied in modern software-intensive systems to ensure
resilience and sustainability, where log parsing is a vital initial step, converting unstructured …
resilience and sustainability, where log parsing is a vital initial step, converting unstructured …
MetaLog: Generalizable Cross-System Anomaly Detection from Logs with Meta-Learning
Log-based anomaly detection plays a crucial role in ensuring the stability of software.
However, current approaches for log-based anomaly detection heavily depend on a vast …
However, current approaches for log-based anomaly detection heavily depend on a vast …