Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
ITran: A novel transformer-based approach for industrial anomaly detection and localization
X Cai, R Xiao, Z Zeng, P Gong, Y Ni - Engineering Applications of Artificial …, 2023 - Elsevier
Anomaly detection is currently an essential quality monitoring process in industrial
production. It is often affected by factors such as under or over reconstruction of images and …
production. It is often affected by factors such as under or over reconstruction of images and …
Deep anomaly detection for time-series data in industrial IoT: A communication-efficient on-device federated learning approach
Since edge device failures (ie, anomalies) seriously affect the production of industrial
products in Industrial IoT (IIoT), accurately and timely detecting anomalies are becoming …
products in Industrial IoT (IIoT), accurately and timely detecting anomalies are becoming …
An intelligent outlier detection method with one class support tucker machine and genetic algorithm toward big sensor data in internet of things
X Deng, P Jiang, X Peng, C Mi - IEEE Transactions on Industrial …, 2018 - ieeexplore.ieee.org
Various types of sensor data can be collected by the Internet of Things (IoT). Each sensor
node has spatial attributes and may also be associated with a large number of measurement …
node has spatial attributes and may also be associated with a large number of measurement …
BTAD: A binary transformer deep neural network model for anomaly detection in multivariate time series data
M Ma, L Han, C Zhou - Advanced Engineering Informatics, 2023 - Elsevier
In the context of big data, if the task of multivariate time series data anomaly detection cannot
be performed efficiently and accurately, it will bring great security risks to industrial systems …
be performed efficiently and accurately, it will bring great security risks to industrial systems …
Light-weight federated learning-based anomaly detection for time-series data in industrial control systems
With the emergence of the Industrial Internet of Things (IIoT), potential threats to smart
manufacturing systems are increasingly becoming challenging, causing severe damage to …
manufacturing systems are increasingly becoming challenging, causing severe damage to …
Complementary set variational autoencoder for supervised anomaly detection
Anomalies have broad patterns corresponding to their causes. In industry, anomalies are
typically observed as equipment failures. Anomaly detection aims to detect such failures as …
typically observed as equipment failures. Anomaly detection aims to detect such failures as …
Physics-informed gated recurrent graph attention unit network for anomaly detection in industrial cyber-physical systems
W Wu, C Song, J Zhao, Z Xu - Information Sciences, 2023 - Elsevier
Industrial cyber-physical systems (ICPSs) play an important role in many critical
infrastructures. To ensure the secure and reliable operation of ICPSs, this work presents a …
infrastructures. To ensure the secure and reliable operation of ICPSs, this work presents a …
Real-time deep anomaly detection framework for multivariate time-series data in industrial iot
H Nizam, S Zafar, Z Lv, F Wang, X Hu - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
The data produced by millions of connected devices and smart sensors in the Industrial
Internet of Things (IIoT) is highly dynamic, large-scale, heterogeneous, and time-stamped …
Internet of Things (IIoT) is highly dynamic, large-scale, heterogeneous, and time-stamped …
Metaheuristic feature selection with deep learning enabled cascaded recurrent neural network for anomaly detection in Industrial Internet of Things environment
N Chander, M Upendra Kumar - Cluster Computing, 2023 - Springer
Abstract Industrial Internet of Things (IIoT) acts as essential part of the revolutionary
transition of conventional industries towards Industry 4.0. By the integration of instruments …
transition of conventional industries towards Industry 4.0. By the integration of instruments …