S-KDGAN: Series-Knowledge Distillation with GANs for Anomaly Detection of Sensor Time-Series Data in Smart IoT

W Cheng, Y Li, T Ma - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Nowadays, smart Internet of Things (IoT) technology as a new paradigm has been widely
used in different fields of our lives. Massive amounts of high-dimensional time-series data …

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 …

Imposters among us: A supervised learning approach to anomaly detection in iot sensor data

T Das, RM ShuklaT, S Sengupta - … on Internet of Things (WF-IoT …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) technology has made smart homes more prevalent in everyday lives.
However, anomalies in IoT data may be emblematic of potential cybersecurity risks like false …

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 …

TinyAD: Memory-Efficient Anomaly Detection for Time-Series Data in Industrial IoT

Y Sun, T Chen, QVH Nguyen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Monitoring and detecting abnormal events in cyber-physical systems is crucial to industrial
production. With the prevalent deployment of the industrial Internet of Things (IIoTs), an …

Anomaly Detection for Industrial Sensors Using Transformers

M Yassine, F Théo - … Conference on Future Internet of Things …, 2023 - ieeexplore.ieee.org
Anomaly detection is a critical task in many domains, including the Internet of Things (IoT),
where large volumes of sensor data are generated from various devices. Traditional …

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 …

Analysis of deep learning models for anomaly detection in time series IoT sensor data

U Sachdeva, PR Vamsi - Proceedings of the 2022 Fourteenth …, 2022 - dl.acm.org
The anomaly detection in Internet of Things (IoT) sensor data has become an important
research area because of the possibility of noise and unavailability of labels in the sensors …

IoT-GAN: Anomaly Detection for Time Series in IoT Based on Generative Adversarial Networks

X Chen, S Zhang, Q Jiang, J Chen, H Huang… - … on Algorithms and …, 2021 - Springer
In order to monitor the behaviors of IoT devices, a large amount of time series data are
collected by sensors embedded in them. To take timely action further to resolve the …

Anomaly Detection on Time series Sensor Data Using Deep LSTM-Autoencoder

S Githinji, CW Maina - 2023 IEEE AFRICON, 2023 - ieeexplore.ieee.org
Anomaly detection is crucial in various applications (eg, cybersecurity, manufacturing,
finance, IoT), and an automatic and reliable anomaly detection tool is necessary for accurate …