Deep Learning Approaches for Network Traffic Classification in the Internet of Things (IoT): A Survey
The Internet of Things (IoT) has witnessed unprecedented growth, resulting in a massive
influx of diverse network traffic from interconnected devices. Effectively classifying this …
influx of diverse network traffic from interconnected devices. Effectively classifying this …
Prediction of gas drainage changes from nitrogen replacement: A study of a TCN deep learning model with integrated attention mechanism
H Xue, X Gui, G Wang, X Yang, H Gong, F Du - Fuel, 2024 - Elsevier
Accurate prediction of pure gas volume changes in nitrogen injection replacement coal
seams is of great significance to increase coalbed methane (CBM) production and prevent …
seams is of great significance to increase coalbed methane (CBM) production and prevent …
Threat analysis model to control IoT network routing attacks through deep learning approach
K Janani, S Ramamoorthy - Connection Science, 2022 - Taylor & Francis
Most of the recent research has focused on the Internet of Things (IoT) and its applications.
The open interface and network connectivity of the interconnected systems under the IoT …
The open interface and network connectivity of the interconnected systems under the IoT …
An intelligent multiclass deep classifier‐based intrusion detection system for cloud environment
R Bingu, S Jothilakshmi… - … and Computation: Practice …, 2023 - Wiley Online Library
The intrusion detection process is considered an efficient mechanism that plays a prominent
role in network security. Traditional approaches for attack detection, like signature‐based …
role in network security. Traditional approaches for attack detection, like signature‐based …
Augmented Intelligence of Things for Emergency Vehicle Secure Trajectory Prediction and Task Offloading
X Wu, J Dong, W Bao, B Zou, L Wang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Augmented Intelligence of Things (AIoT) combines augmented intelligence algorithms with
the massive data collected by IoT devices, enabling more advanced decision-making. The …
the massive data collected by IoT devices, enabling more advanced decision-making. The …
[HTML][HTML] FSL: federated sequential learning-based cyberattack detection for Industrial Internet of Things
F Li, J Lin, H Han - Industrial Artificial Intelligence, 2023 - Springer
Abstract Industrial Internet of Things (IIoT) brings revolutionary technical supports to modern
industries. However, today's IIoT still faces the challenges of modeling varying time-series in …
industries. However, today's IIoT still faces the challenges of modeling varying time-series in …
[PDF][PDF] Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach.
AR Zarzoor, NAS Al-Jamali… - … Modelling of Engineering …, 2023 - researchgate.net
Accepted: 13 March 2023 Whenever, the Internet of Things (IoT) applications and devices
increased, the capability of the its access frequently stressed. That can lead a significant …
increased, the capability of the its access frequently stressed. That can lead a significant …
LightFIDS: Lightweight and Hierarchical Federated IDS for Massive IoT in 6G Network
A Alotaibi, A Barnawi - Arabian Journal for Science and Engineering, 2024 - Springer
IoT traffic on access networks is expected to increase significantly with the advent of 6G-
enabled massive IoT networks. Nevertheless, current intrusion detection system (IDS) …
enabled massive IoT networks. Nevertheless, current intrusion detection system (IDS) …
Machine vision and novel attention mechanism TCN for enhanced prediction of future deposition height in directed energy deposition
Abstract Laser Directed Energy Deposition (L-DED) has garnered significant attention due to
its high flexibility and rapid processing capabilities. However, complex physical flow fields …
its high flexibility and rapid processing capabilities. However, complex physical flow fields …
A dynamic global backbone updating for communication-efficient personalised federated learning
Z Yang, Q Sun - Connection Science, 2022 - Taylor & Francis
Federated learning (FL) is an emerging distributed machine learning technique. However,
when dealing with heterogeneous data, a shared global model cannot generalise all …
when dealing with heterogeneous data, a shared global model cannot generalise all …