A unifying review of deep and shallow anomaly detection
Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …
the art in detection performance on complex data sets, such as large collections of images or …
[HTML][HTML] Deep learning for anomaly detection in log data: A survey
Automatic log file analysis enables early detection of relevant incidents such as system
failures. In particular, self-learning anomaly detection techniques capture patterns in log …
failures. In particular, self-learning anomaly detection techniques capture patterns in log …
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 …
Log-based anomaly detection without log parsing
Software systems often record important runtime information in system logs for
troubleshooting purposes. There have been many studies that use log data to construct …
troubleshooting purposes. There have been many studies that use log data to construct …
Lanobert: System log anomaly detection based on bert masked language model
The system log generated in a computer system refers to large-scale data that are collected
simultaneously and used as the basic data for determining errors, intrusion and abnormal …
simultaneously and used as the basic data for determining errors, intrusion and abnormal …
Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review
Globally, the external internet is increasingly being connected to industrial control systems.
As a result, there is an immediate need to protect these networks from a variety of threats …
As a result, there is an immediate need to protect these networks from a variety of threats …
[PDF][PDF] Unifying the perspectives of nlp and software engineering: A survey on language models for code
Z Zhang, C Chen, B Liu, C Liao, Z Gong… - arxiv preprint arxiv …, 2023 - simg.baai.ac.cn
In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …
Ai for it operations (aiops) on cloud platforms: Reviews, opportunities and challenges
Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big
data generated by IT Operations processes, particularly in cloud infrastructures, to provide …
data generated by IT Operations processes, particularly in cloud infrastructures, to provide …
Log-based anomaly detection with robust feature extraction and online learning
S Han, Q Wu, H Zhang, B Qin, J Hu… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Cloud technology has brought great convenience to enterprises as well as customers.
System logs record notable events and are becoming valuable resources to track and …
System logs record notable events and are becoming valuable resources to track and …
Deepsyslog: Deep anomaly detection on syslog using sentence embedding and metadata
Anomaly events indicating the unhealthy status of the computer system are recorded in the
system log (Syslog). Therefore, Syslog-based anomaly event detection is crucial for …
system log (Syslog). Therefore, Syslog-based anomaly event detection is crucial for …