[HTML][HTML] A systematic literature review on machine learning and deep learning approaches for detecting DDoS attacks in software-defined networking

AA Bahashwan, M Anbar, S Manickam, TA Al-Amiedy… - Sensors, 2023 - mdpi.com
Software-defined networking (SDN) is a revolutionary innovation in network technology with
many desirable features, including flexibility and manageability. Despite those advantages …

[PDF][PDF] Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review

H Kheddar, Y Himeur, AI Awad - arXiv preprint arXiv …, 2023 - research.uaeu.ac.ae
Globally, the external Internet is increasingly being connected to the contemporary industrial
control system. As a result, there is an immediate need to protect the network from several …

[HTML][HTML] Convolutional neural networks: A survey

M Krichen - Computers, 2023 - mdpi.com
Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …

Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system

V Ravi, R Chaganti, M Alazab - Computers and Electrical Engineering, 2022 - Elsevier
This work proposes an end-to-end model for network attack detection and network attack
classification using deep learning-based recurrent models. The proposed model extracts the …

Design and development of RNN anomaly detection model for IoT networks

I Ullah, QH Mahmoud - IEEE Access, 2022 - ieeexplore.ieee.org
Cybersecurity is important today because of the increasing growth of the Internet of Things
(IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber …

A flow-based anomaly detection approach with feature selection method against ddos attacks in sdns

MS El Sayed, NA Le-Khac, MA Azer… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Software Defined Networking (SDN) is an emerging network platform, which facilitates
centralised network management. The SDN enables the network operators to manage the …

[HTML][HTML] Deep learning approach for SDN-enabled intrusion detection system in IoT networks

R Chaganti, W Suliman, V Ravi, A Dua - Information, 2023 - mdpi.com
Owing to the prevalence of the Internet of things (IoT) devices connected to the Internet, the
number of IoT-based attacks has been growing yearly. The existing solutions may not …

[HTML][HTML] ID-RDRL: a deep reinforcement learning-based feature selection intrusion detection model

K Ren, Y Zeng, Z Cao, Y Zhang - Scientific reports, 2022 - nature.com
Network assaults pose significant security concerns to network services; hence, new
technical solutions must be used to enhance the efficacy of intrusion detection systems …

[HTML][HTML] DIDS: A Deep Neural Network based real-time Intrusion detection system for IoT

M Vishwakarma, N Kesswani - Decision Analytics Journal, 2022 - Elsevier
The number of people using the Internet of Things (IoT) devices has exploded in recent
years. The instantaneous development in deploying constrained devices in numerous areas …

FMDADM: A multi-layer DDoS attack detection and mitigation framework using machine learning for stateful SDN-based IoT networks

WI Khedr, AE Gouda, ER Mohamed - IEEE Access, 2023 - ieeexplore.ieee.org
The absence of standards and the diverse nature of the Internet of Things (IoT) have made
security and privacy concerns more acute. Attacks such as distributed denial of service …