Incentive techniques for the internet of things: a survey
Abstract The Internet of Things (IoT) has remarkably evolved over the last few years to
realize a wide range of newly emerging services and applications empowered by the …
realize a wide range of newly emerging services and applications empowered by the …
Intelligent traffic management in next-generation networks
The recent development of smart devices has lead to an explosion in data generation and
heterogeneity. Hence, current networks should evolve to become more intelligent, efficient …
heterogeneity. Hence, current networks should evolve to become more intelligent, efficient …
F-bids: Federated-blending based intrusion detection system
The rapid development of network communication along with the drastic increase in the
number of smart devices has triggered a surge in network traffic, which can contain private …
number of smart devices has triggered a surge in network traffic, which can contain private …
An ensemble-based machine learning model for forecasting network traffic in VANET
PAD Amiri, S Pierre - IEEE Access, 2023 - ieeexplore.ieee.org
Vehicular Ad-hoc Networks (VANETs), as the most significant element of the Intelligent
Transportation Systems (ITS), have the potential to enhance traffic efficiency and road safety …
Transportation Systems (ITS), have the potential to enhance traffic efficiency and road safety …
Ensemble-based deep learning model for network traffic classification
Network Traffic Classification enables a number of practical applications ranging from
network monitoring to resource management, with security implications as well. Nowadays …
network monitoring to resource management, with security implications as well. Nowadays …
Network traffic analysis using machine learning: an unsupervised approach to understand and slice your network
Recent development in smart devices has lead us to an explosion in data generation and
heterogeneity, which requires new network solutions for better analyzing and understanding …
heterogeneity, which requires new network solutions for better analyzing and understanding …
Deep Neural Decision Forest (DNDF): A Novel Approach for Enhancing Intrusion Detection Systems in Network Traffic Analysis
Intrusion detection systems, also known as IDSs, are widely regarded as one of the most
essential components of an organization's network security. This is because IDSs serve as …
essential components of an organization's network security. This is because IDSs serve as …
A hybrid CNN-LSTM model for IIoT edge privacy-aware intrusion detection
EM de Elias, VS Carriel, GW De Oliveira… - 2022 IEEE Latin …, 2022 - ieeexplore.ieee.org
Security is a critical issue in the context of IoT and, more recently, of Industrial IoT (IIoT)
environments. To mitigate security threats, Intrusion Detection Systems have been …
environments. To mitigate security threats, Intrusion Detection Systems have been …
Performance Comparison of Ensemble Learning and Supervised Algorithms in Classifying Multi-label Network Traffic Flow
Network traffic classification is of significant importance. It helps identify network anomalies
and assists in taking measures to avoid them. However, classifying network traffic correctly is …
and assists in taking measures to avoid them. However, classifying network traffic correctly is …
Handling partially labeled network data: A semi-supervised approach using stacked sparse autoencoder
Network traffic analytics has become a crucial task in order to better understand and
manage network resources, especially in the network softwarization era where the …
manage network resources, especially in the network softwarization era where the …