The era of big data, which is coming with a complicated and big scope of data, has caused
the increase of the possibility of network attack. One of those possible attacks is DDoS or …

Network attacks of the distributed denial of service (DDoS) form are used to disrupt server
replies and services. It is popular because it is easy to set up and challenging to detect. We …

Abstract Distributed Denial of Service (DDoS) attack is a stubborn network security problem.
Various machine learning-based methods have been proposed to detect such attacks …

Advances in technology and the rapid development of the internet have created more
opportunities for hackers to obtain information and data, creating the need to protect more …

Being used to target a single system or website with overwhelming traffic. This can cause the
system or website to become unavailable to legitimate users. DDoS attacks are often used to …

Abstract Distributed Denial of Service (DDoS) attacks continue to be the most dangerous
over the Internet. With the rapid advancement of information and communication technology …

Recent trends have revealed that DDoS attacks contribute to the majority of overall network
attacks. Networks face challenges in distinguishing between legitimate and malicious flows …

A broad increase in data consumption in society and industry trigger network operators
looking to upgrade their metro networks with higher bandwidth requirements. Service …

Abstract Distributed Denial of Service (DDoS) attacks are a weapon of choice for hackers
that are accountable for degradation in network performance, website downtime, and …

Machine learning (ML) is used for network intrusion detection because it is predictable after
training with relevant data. ML provides a great way to detect new and unknown attacks …