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 …
An evolutionary SVM model for DDOS attack detection in software defined networks
Software-Defined Network (SDN) has become a promising network architecture in current
days that provide network operators more control over the network infrastructure. The …
days that provide network operators more control over the network infrastructure. The …
Detecting DDoS attacks using adversarial neural network
Abstract In a Distributed Denial of Service (DDoS) attack, a network of compromised devices
is used to overwhelm a target with a flood of requests, making it unable to serve legitimate …
is used to overwhelm a target with a flood of requests, making it unable to serve legitimate …
An investigation into the application of deep learning in the detection and mitigation of DDOS attack on SDN controllers
Software-Defined Networking (SDN) is a new paradigm that revolutionizes the idea of a
software-driven network through the separation of control and data planes. It addresses the …
software-driven network through the separation of control and data planes. It addresses the …
[PDF][PDF] DDoS Detection in SDN using Machine Learning Techniques.
Software-defined network (SDN) becomes a new revolutionary paradigm in networks
because it provides more control and network operation over a network infrastructure. The …
because it provides more control and network operation over a network infrastructure. The …
A hybrid deep learning approach for bottleneck detection in IoT
Cloud computing is perhaps the most enticing innovation in the present figuring situation. It
gives an expense-effective arrangement by diminishing the enormous forthright expense of …
gives an expense-effective arrangement by diminishing the enormous forthright expense of …
Use of machine learning for Web Denial-of-service attacks: a multivocal literature review
Abstract Denial-of-service (DoS) attacks conducted on online systems cause the targeted
resources to become inoperative. This is caused by the abnormal traffic intentionally …
resources to become inoperative. This is caused by the abnormal traffic intentionally …
Detecting and mitigating DDoS attacks with moving target defense approach based on automated flow classification in SDN networks
Abstract The Distributed Denial of Service (DDoS) coordinates synchronized attacks on
systems on the Internet using a set of infected hosts (bots). Bots are programmed to attack a …
systems on the Internet using a set of infected hosts (bots). Bots are programmed to attack a …
A comprehensive analysis of machine learning-and deep learning-based solutions for DDoS attack detection in SDN
Software-defined networking (SDN) provides programmability, manageability, flexibility and
efficiency compared to traditional networks. These are owing to the SDN's mutual …
efficiency compared to traditional networks. These are owing to the SDN's mutual …
Enhanced security against volumetric DDoS attacks using adversarial machine learning
With the increasing number of Internet users, cybersecurity is becoming more and more
critical. Denial of service (DoS) and distributed denial of service (DDoS) attacks are two of …
critical. Denial of service (DoS) and distributed denial of service (DDoS) attacks are two of …