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 …
Machine-learning-based DDoS attack detection using mutual information and random forest feature importance method
Cloud computing facilitates the users with on-demand services over the Internet. The
services are accessible from anywhere at any time. Despite the valuable services, the …
services are accessible from anywhere at any time. Despite the valuable services, the …
Optimization of RBF-SVM kernel using grid search algorithm for DDoS attack detection in SDN-based VANET
The dynamic nature of the vehicular space exposes it to distributed malicious attacks
irrespective of the integration of enabling technologies. The software-defined network (SDN) …
irrespective of the integration of enabling technologies. The software-defined network (SDN) …
RBF-SVM kernel-based model for detecting DDoS attacks in SDN integrated vehicular network
The development of the intelligent transport space (ITS) comes with the challenge of
securing transportation data. As the vehicular network is highly dynamic, the network …
securing transportation data. As the vehicular network is highly dynamic, the network …
Impact of feature selection methods on machine learning-based for detecting DDoS attacks: Literature review
Cybersecurity attacks are becoming increasingly sophisticated and increasing with the
development of technology so that they present threats to both the private and public …
development of technology so that they present threats to both the private and public …
Deep learning based hybrid intrusion detection systems to protect satellite networks
Despite the fact that satellite-terrestrial systems have advantages such as high throughput,
low latency, and low energy consumption, as well as low exposure to physical threats and …
low latency, and low energy consumption, as well as low exposure to physical threats and …
Federated learning inspired low-complexity intrusion detection and classification technique for sdn-based industrial cps
Unauthorized users may attack centralized controllers as an attractive target in software-
defined networking (SDN)-based industrial cyber-physical systems (CPS). Managing high …
defined networking (SDN)-based industrial cyber-physical systems (CPS). Managing high …
An efficient approach to detect distributed denial of service attacks for software defined internet of things combining autoencoder and extreme gradient boosting with …
MA Setitra, M Fan… - Transactions on Emerging …, 2023 - Wiley Online Library
The growing popularity of Software Defined Networks (SDN) and the Internet of Things (IoT)
has led to the emergence of Software Defined Internet of Things (SDIoT) based on …
has led to the emergence of Software Defined Internet of Things (SDIoT) based on …
Machine learning assisted snort and zeek in detecting DDoS attacks in software-defined networking
A new network architecture called the Software-Defined Network (SDN) gives next-
generation networks a more flexible and efficiently controlled network architecture. Using the …
generation networks a more flexible and efficiently controlled network architecture. Using the …
Attack detection analysis in software-defined networks using various machine learning method
Y Wang, X Wang, MM Ariffin, M Abolfathi… - Computers and …, 2023 - Elsevier
Abstract The Software-Defined Network (SDN) provides a more flexible and effectively
managed network design for next-generation networking. Network managers can easily …
managed network design for next-generation networking. Network managers can easily …