Machine learning techniques in emerging cloud computing integrated paradigms: A survey and taxonomy
Cloud computing offers Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and
Software as a Service (SaaS) to provide compute, network, and storage capabilities to the …
Software as a Service (SaaS) to provide compute, network, and storage capabilities to the …
A systematic literature review on machine learning and deep learning approaches for detecting DDoS attacks in software-defined networking
Software-defined networking (SDN) is a revolutionary innovation in network technology with
many desirable features, including flexibility and manageability. Despite those advantages …
many desirable features, including flexibility and manageability. Despite those advantages …
[HTML][HTML] Towards a machine learning-based framework for DDOS attack detection in software-defined IoT (SD-IoT) networks
Abstract The Internet of Things (IoT) is a complex and diverse network consisting of resource-
constrained sensors/devices/things that are vulnerable to various security threats …
constrained sensors/devices/things that are vulnerable to various security threats …
Deep learning-based intrusion detection for distributed denial of service attack in agriculture 4.0
Smart Agriculture or Agricultural Internet of things, consists of integrating advanced
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
technologies (eg, NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm …
A new DDoS attacks intrusion detection model based on deep learning for cybersecurity
The data is exposed to many attacks during communication in the network environment. It is
becoming increasingly essential to identify intrusions into network communications …
becoming increasingly essential to identify intrusions into network communications …
Cyber security for detecting distributed denial of service attacks in agriculture 4.0: Deep learning model
THH Aldhyani, H Alkahtani - Mathematics, 2023 - mdpi.com
Attackers are increasingly targeting Internet of Things (IoT) networks, which connect
industrial devices to the Internet. To construct network intrusion detection systems (NIDSs) …
industrial devices to the Internet. To construct network intrusion detection systems (NIDSs) …
Ae-mlp: A hybrid deep learning approach for ddos detection and classification
Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet
connectivity massively grows in recent years. Conventional shallow machine learning-based …
connectivity massively grows in recent years. Conventional shallow machine learning-based …
An efficient hybrid-dnn for ddos detection and classification in software-defined iiot networks
Software-defined networking (SDN)-based Industrial Internet of Things (IIoT) networks have
a centralized controller that is a single attractive target for unauthorized users to attack …
a centralized controller that is a single attractive target for unauthorized users to attack …
Machine-learning-enabled ddos attacks detection in p4 programmable networks
Abstract Distributed Denial of Service (DDoS) attacks represent a major concern in modern
Software Defined Networking (SDN), as SDN controllers are sensitive points of failures in …
Software Defined Networking (SDN), as SDN controllers are sensitive points of failures in …
Robust detection of unknown DoS/DDoS attacks in IoT networks using a hybrid learning model
The fourth industrial revolution is marked by the rapid growth of Internet of Things (IoT)
technology, leading to an increase in the number of IoT devices. Unfortunately, this also …
technology, leading to an increase in the number of IoT devices. Unfortunately, this also …