Ensemble learning for intrusion detection in sdn-based zero touch smart grid systems

Z Abou El Houda, B Brik… - 2022 IEEE 47th …, 2022 - ieeexplore.ieee.org
Software-defined network (SDN) is widely deployed on Smart Grid (SG) systems. It consists
in decoupling control and data planes, to automate the monitoring and management of the …

Internet of things intrusion detection: Centralized, on-device, or federated learning?

SA Rahman, H Tout, C Talhi, A Mourad - IEEE Network, 2020 - ieeexplore.ieee.org
With the ever increasing number of cyber-attacks, internet of Things (ioT) devices are being
exposed to serious malware, attacks, and malicious activities alongside their development …

Machine learning-based intrusion detection for smart grid computing: A survey

N Sahani, R Zhu, JH Cho, CC Liu - ACM Transactions on Cyber-Physical …, 2023 - dl.acm.org
Machine learning (ML)-based intrusion detection system (IDS) approaches have been
significantly applied and advanced the state-of-the-art system security and defense …

Federated learning-based intrusion detection in SDN-enabled IIoT networks

PT Duy, T Van Hung, NH Ha… - … on Information and …, 2021 - ieeexplore.ieee.org
Witnessing the explosion in the number of Internet of Things (IoTs) in industries, Software
Defined Networking (SDN) is considered as a flexible, efficient, and programmable …

Deep learning and software-defined networks: Towards secure IoT architecture

A Dawoud, S Shahristani, C Raun - Internet of Things, 2018 - Elsevier
Abstract Internet of Things (IoT) introduces new challenges to conventional communication
model. IoT networks characteristics, such as objects heterogeneity and scalability, require …

A novel sdn dataset for intrusion detection in iot networks

AK Sarica, P Angin - 2020 16th International Conference on …, 2020 - ieeexplore.ieee.org
The number of Internet of Things (IoT) devices and the use cases they aim to support have
increased sharply in the past decade with the rapid developments in wireless networking …

Intrusion Detection System in Software-Defined Networks Using Machine Learning and Deep Learning Techniques--A Comprehensive Survey

MR Ahmed, S Shatabda, AKMM Islam, MTI Robin - Authorea Preprints, 2023 - techrxiv.org
At present, the Internet is facing numerous attacks of different kinds that put its data at risk.
The safety of information within the network is, therefore, a significant concern. To prevent …

Deep learning feature fusion approach for an intrusion detection system in SDN-based IoT networks

V Ravi, R Chaganti, M Alazab - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
A survey of the literature shows that the number of IoT attacks are gradually growing over the
years due to the growing trend of Internet-enabled devices. Software defined networking …

[HTML][HTML] DeepIDS: Deep learning approach for intrusion detection in software defined networking

TA Tang, L Mhamdi, D McLernon, SAR Zaidi… - Electronics, 2020 - mdpi.com
Software Defined Networking (SDN) is developing as a new solution for the development
and innovation of the Internet. SDN is expected to be the ideal future for the Internet, since it …

Fine-tuned LSTM-based model for efficient honeypot-based network intrusion detection system in smart grid networks

A Albaseer, M Abdallah - 2022 5th international conference on …, 2022 - ieeexplore.ieee.org
Honeypot is considered a powerful complement to the Network Intrusion Detection System
(NIDS) in smart grid (SG) systems, which minimizes the workload of NIDSs while providing …