Try with Simpler - An Evaluation of Improved Principal Component Analysis in Log-based Anomaly Detection
Abstract
References
Index Terms
- Try with Simpler - An Evaluation of Improved Principal Component Analysis in Log-based Anomaly Detection
Recommendations
Log-based anomaly detection with deep learning: how far are we?
ICSE '22: Proceedings of the 44th International Conference on Software EngineeringSoftware-intensive systems produce logs for troubleshooting purposes. Recently, many deep learning models have been proposed to automatically detect system anomalies based on log data. These models typically claim very high detection accuracy. For ...
Deep Learning or Classical Machine Learning? An Empirical Study on Log-Based Anomaly Detection
ICSE '24: Proceedings of the IEEE/ACM 46th International Conference on Software EngineeringWhile deep learning (DL) has emerged as a powerful technique, its benefits must be carefully considered in relation to computational costs. Specifically, although DL methods have achieved strong performance in log anomaly detection, they often require ...
Robust log-based anomaly detection on unstable log data
ESEC/FSE 2019: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software EngineeringLogs are widely used by large and complex software-intensive systems for troubleshooting. There have been a lot of studies on log-based anomaly detection. To detect the anomalies, the existing methods mainly construct a detection model using log event ...
Comments
Information & Contributors
Information
Published In
![cover image ACM Transactions on Software Engineering and Methodology](/cms/asset/4a0213fc-1fcc-4d3d-8ff9-2393c5cc110f/3618079.cover.jpg)
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- National Natural Science Foundation of China
- CCF Young Elite Scientists Sponsorship Program (by CAST)
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 282Total Downloads
- Downloads (Last 12 months)282
- Downloads (Last 6 weeks)71
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in