Mfgan: multimodal fusion for industrial anomaly detection using attention-based autoencoder and generative adversarial network
Anomaly detection plays a critical role in ensuring safe, smooth, and efficient operation of
machinery and equipment in industrial environments. With the wide deployment of …
machinery and equipment in industrial environments. With the wide deployment of …
Deep learning-enabled anomaly detection for IoT systems
Abstract Internet of Things (IoT) systems have become an intrinsic technology in various
industries and government services. Unfortunately, IoT devices and networks are known to …
industries and government services. Unfortunately, IoT devices and networks are known to …
An efficient framework for unsupervised anomaly detection over edge-assisted internet of things
Y Liu, H Wang, X Zheng, L Tian - ACM Transactions on Sensor Networks, 2023 - dl.acm.org
The detection of anomaly status plays a pivotal role in the maintenance of public
transportation and facilities in smart cities. Owing to the pervasively deployed sensing …
transportation and facilities in smart cities. Owing to the pervasively deployed sensing …
MTS-DVGAN: Anomaly detection in cyber-physical systems using a dual variational generative adversarial network
H Sun, Y Huang, L Han, C Fu, H Liu, X Long - Computers & Security, 2024 - Elsevier
Deep generative models are promising in detecting novel cyber-physical attacks, mitigating
the vulnerability of Cyber-physical systems (CPSs) without relying on labeled information …
the vulnerability of Cyber-physical systems (CPSs) without relying on labeled information …
An explainable ensemble deep learning approach for intrusion detection in industrial Internet of Things
Ensuring the security of critical Industrial Internet of Things (IIoT) systems is of utmost
importance, with a primary focus on identifying cyber-attacks using Intrusion Detection …
importance, with a primary focus on identifying cyber-attacks using Intrusion Detection …
Anomaly detection using deep neural network for IoT architecture
The revolutionary idea of the internet of things (IoT) architecture has gained enormous
popularity over the last decade, resulting in an exponential growth in the IoT networks …
popularity over the last decade, resulting in an exponential growth in the IoT networks …
Scalable anomaly-based intrusion detection for secure Internet of Things using generative adversarial networks in fog environment
W Yao, H Shi, H Zhao - Journal of Network and Computer Applications, 2023 - Elsevier
The data generated exponentially by a massive number of devices in the Internet of Things
(IoT) are extremely high-dimensional, large-scale, non-labeled, which poses great …
(IoT) are extremely high-dimensional, large-scale, non-labeled, which poses great …
Hybrid Framework Combining Deep Learning and Grey Wolf Optimizer for Anomaly Detection in IoT-Enabled Systems
B Selvakumar, B Lakshmanan… - Soft Computing: Theories …, 2022 - Springer
This proposed work presents an efficient anomaly detection framework based on deep
learning combined grey wolf optimizer for anomaly detection. Despite rapid advancements …
learning combined grey wolf optimizer for anomaly detection. Despite rapid advancements …
A Comparative Study of Anomaly Detection Techniques for IoT Security using AMoT (Adaptive Machine Learning for IoT Threats)
D Alsalman - IEEE Access, 2024 - ieeexplore.ieee.org
Anomaly detection is a critical aspect of various applications, including security, healthcare,
and network monitoring. In this study, we introduce FusionNet, an innovative ensemble …
and network monitoring. In this study, we introduce FusionNet, an innovative ensemble …
IDG-SemiAD: An Immune Detector Generation-Based Collaborative Learning Scheme for Semi-supervised Anomaly Detection in Industrial Cyber-physical Systems
Anomaly detection is a critical line of defense to ensure the network security of industrial
cyber-physical systems. However, a significant issue in the anomaly detection is the …
cyber-physical systems. However, a significant issue in the anomaly detection is the …