Detection and mitigation of DDoS attacks in SDN: A comprehensive review, research challenges and future directions
Many security solutions have been proposed in the past to protect Internet architecture from
a diversity of malware. However, the security of the Internet and its applications is still an …
a diversity of malware. However, the security of the Internet and its applications is still an …
Towards DDoS detection mechanisms in software-defined networking
Y Cui, Q Qian, C Guo, G Shen, Y Tian, H Xing… - Journal of Network and …, 2021 - Elsevier
Abstract Software-Defined Networking (SDN) is widely considered as one of the next
generation network architecture. However, SDN faces with a series of issues which restraint …
generation network architecture. However, SDN faces with a series of issues which restraint …
Ddosnet: A deep-learning model for detecting network attacks
MS Elsayed, NA Le-Khac, S Dev… - 2020 IEEE 21st …, 2020 - ieeexplore.ieee.org
Software-Defined Networking (SDN) is an emerging paradigm, which evolved in recent
years to address the weaknesses in traditional networks. The significant feature of the SDN …
years to address the weaknesses in traditional networks. The significant feature of the SDN …
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 …
centralised network management. The SDN enables the network operators to manage the …
Detecting DDoS attacks in software-defined networks through feature selection methods and machine learning models
Software Defined Networking (SDN) offers several advantages such as manageability,
scaling, and improved performance. However, SDN involves specific security problems …
scaling, and improved performance. However, SDN involves specific security problems …
Machine learning in network anomaly detection: A survey
S Wang, JF Balarezo, S Kandeepan… - IEEE …, 2021 - ieeexplore.ieee.org
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …
networks against malicious access is always challenging even though it has been studied …
Collaborative prediction and detection of DDoS attacks in edge computing: A deep learning-based approach with distributed SDN
Edge computing (EC) has greatly facilitated the deployment of networked services with fast
responses and low bandwidth, by deploying computing and storage at the network edge …
responses and low bandwidth, by deploying computing and storage at the network edge …
Software-defined networking-based DDoS defense mechanisms
Distributed Denial of Service attack (DDoS) is recognized to be one of the most catastrophic
attacks against various digital communication entities. Software-defined networking (SDN) is …
attacks against various digital communication entities. Software-defined networking (SDN) is …
DDoS attack and detection methods in internet-enabled networks: Concept, research perspectives, and challenges
In recent times, distributed denial of service (DDoS) has been one of the most prevalent
security threats in internet-enabled networks, with many internet of things (IoT) devices …
security threats in internet-enabled networks, with many internet of things (IoT) devices …
A DDoS attack mitigation scheme in ISP networks using machine learning based on SDN
Keeping Internet users protected from cyberattacks and other threats is one of the most
prominent security challenges for network operators nowadays. Among other critical threats …
prominent security challenges for network operators nowadays. Among other critical threats …