It infrastructure anomaly detection and failure handling: A systematic literature review focusing on datasets, log preprocessing, machine & deep learning approaches …
DA Bhanage, AV Pawar, K Kotecha - IEEE Access, 2021 - ieeexplore.ieee.org
Nowadays, reliability assurance is crucial in components of IT infrastructures. Unavailability
of any element or connection results in downtime and triggers monetary and performance …
of any element or connection results in downtime and triggers monetary and performance …
Landscape of automated log analysis: A systematic literature review and mapping study
Ł Korzeniowski, K Goczyła - IEEE Access, 2022 - ieeexplore.ieee.org
Logging is a common practice in software engineering to provide insights into working
systems. The main uses of log files have always been failure identification and root cause …
systems. The main uses of log files have always been failure identification and root cause …
System log parsing: A survey
Modern information and communication systems have become increasingly challenging to
manage. The ubiquitous system logs contain plentiful information and are thus widely …
manage. The ubiquitous system logs contain plentiful information and are thus widely …
Logencoder: Log-based contrastive representation learning for anomaly detection
In recent years, cloud computing centers have grown rapidly in size. Analyzing system logs
is an important way for the quality of service monitoring. However, systems produce massive …
is an important way for the quality of service monitoring. However, systems produce massive …
PVE: A log parsing method based on VAE using embedding vectors
W Yuan, S Ying, X Duan, H Cheng, Y Zhao… - Information Processing & …, 2023 - Elsevier
Log parsing is a critical task that converts unstructured raw logs into structured data for
downstream tasks. Existing methods often rely on manual string-matching rules to extract …
downstream tasks. Existing methods often rely on manual string-matching rules to extract …
Failure detection using semantic analysis and attention-based classifier model for IT Infrastructure log data
The improvement in the reliability, availability, and maintenance of the IT infrastructure
components is paramount to ensure uninterrupted services in large-scale IT Infrastructures …
components is paramount to ensure uninterrupted services in large-scale IT Infrastructures …
Automatic parsing and utilization of system log features in log analysis: A survey
J Ma, Y Liu, H Wan, G Sun - Applied Sciences, 2023 - mdpi.com
System logs are almost the only data that records system operation information, so they play
an important role in anomaly analysis, intrusion detection, and situational awareness …
an important role in anomaly analysis, intrusion detection, and situational awareness …
Loggpt: Exploring chatgpt for log-based anomaly detection
The increasing volume of log data produced by software-intensive systems makes it
impractical to analyze them manually. Many deep learning-based methods have been …
impractical to analyze them manually. Many deep learning-based methods have been …
Prefix-graph: A versatile log parsing approach merging prefix tree with probabilistic graph
Logs play an important part in analyzing system behavior and diagnosing system failures.
As the basic step of log analysis, log parsing converts raw log messages into structured log …
As the basic step of log analysis, log parsing converts raw log messages into structured log …
Explainable log parsing and online interval granular classification from streams of words
We introduce a method called evolving Log Parsing (eLP) to extract information granules
and an interval rule-based classification model from streams of words in unstructured log …
and an interval rule-based classification model from streams of words in unstructured log …