Deep anomaly detection for time-series data in industrial IoT: A communication-efficient on-device federated learning approach

Y Liu, S Garg, J Nie, Y Zhang, Z Xiong… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Since edge device failures (ie, anomalies) seriously affect the production of industrial
products in Industrial IoT (IIoT), accurately and timely detecting anomalies are becoming …

Communication-efficient federated learning for anomaly detection in industrial internet of things

Y Liu, N Kumar, Z Xiong, WYB Lim… - … 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
With the rapid development of the Industrial Internet of Things (IIoT), various IoT devices and
sensors generate massive industrial sensing data. Sensing big data can be analyzed for …

Toward accurate anomaly detection in industrial internet of things using hierarchical federated learning

X Wang, S Garg, H Lin, J Hu… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) is an emerging technology that can promote the
development of industrial intelligence, improve production efficiency, and reduce …

Light-weight federated learning-based anomaly detection for time-series data in industrial control systems

HT Truong, BP Ta, QA Le, DM Nguyen, CT Le… - Computers in …, 2022 - Elsevier
With the emergence of the Industrial Internet of Things (IIoT), potential threats to smart
manufacturing systems are increasingly becoming challenging, causing severe damage to …

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 …

LSTM learning with Bayesian and Gaussian processing for anomaly detection in industrial IoT

D Wu, Z Jiang, X Xie, X Wei, W Yu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The data generated by millions of sensors in the industrial Internet of Things (IIoT) are
extremely dynamic, heterogeneous, and large scale and pose great challenges on the real …

[HTML][HTML] An ensemble deep learning model for cyber threat hunting in industrial internet of things

A Yazdinejad, M Kazemi, RM Parizi… - Digital Communications …, 2023 - Elsevier
By the emergence of the fourth industrial revolution, interconnected devices and sensors
generate large-scale, dynamic, and inharmonious data in Industrial Internet of Things (IIoT) …

Integrated generative model for industrial anomaly detection via bidirectional LSTM and attention mechanism

F Kong, J Li, B Jiang, H Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
For emerging industrial Internet of Things (IIoT), intelligent anomaly detection is a key step to
build smart industry. Especially, explosive time-series data pose enormous challenges to the …

Security and privacy-enhanced federated learning for anomaly detection in IoT infrastructures

L Cui, Y Qu, G Xie, D Zeng, R Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) anomaly detection is significant due to its fundamental roles of
securing modern critical infrastructures, such as falsified data injection detection and …

Detecting cyberattacks using anomaly detection in industrial control systems: A federated learning approach

TT Huong, TP Bac, DM Long, TD Luong, NM Dan… - Computers in …, 2021 - Elsevier
In recent years, the rapid development and wide application of advanced technologies have
profoundly impacted industrial manufacturing, leading to smart manufacturing (SM) …