Incentive techniques for the internet of things: a survey

PKR Maddikunta, QV Pham, DC Nguyen… - Journal of Network and …, 2022 - Elsevier
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 …

Intelligent traffic management in next-generation networks

O Aouedi, K Piamrat, B Parrein - Future internet, 2022 - mdpi.com
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 …

F-bids: Federated-blending based intrusion detection system

O Aouedi, K Piamrat - Pervasive and Mobile Computing, 2023 - Elsevier
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 …

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 …

Ensemble-based deep learning model for network traffic classification

O Aouedi, K Piamrat, B Parrein - IEEE Transactions on Network …, 2022 - ieeexplore.ieee.org
Network Traffic Classification enables a number of practical applications ranging from
network monitoring to resource management, with security implications as well. Nowadays …

[HTML][HTML] Deep neural decision forest (DNDF): A novel approach for enhancing intrusion detection systems in network traffic analysis

FS Alrayes, M Zakariah, M Driss, W Boulila - Sensors, 2023 - mdpi.com
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 …

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 …

Network traffic analysis using machine learning: an unsupervised approach to understand and slice your network

O Aouedi, K Piamrat, S Hamma, JKM Perera - Annals of …, 2022 - Springer
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 …

Performance comparison of ensemble learning and supervised algorithms in classifying multi-label network traffic flow

M Machoke, J Mbelwa, J Agbinya, AE Sam - Engineering, Technology & …, 2022 - etasr.com
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 …

AF-FDS: An accurate, fast, and fine-grained detection scheme for DDoS attacks in high-speed networks with asymmetric routing

Z Shao, T Chen, G Cheng, X Hu, W Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks have posed severe threats to the Internet.
Although researchers have proposed many DDoS detection schemes, there are still some …