Deep learning (DL) is gaining significant prevalence in every field of study due to its
domination in training large data sets. However, several applications are utilizing machine …

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 …

The key objective of a Distributed Denial of Service (DDoS) attack is to compile multiple
systems across the Internet with infected zombies/agents and form botnets of networks. Such …

Cloud computing is a revolution in IT technology that provides scalable, virtualized on-
demand resources to the end users with greater flexibility, less maintenance and reduced …

While software defined network (SDN) brings more innovation to the development of future
networks, it also faces a more severe threat from DDoS attacks. In order to deal with the …

Abstract Even though advanced Machine Learning (ML) techniques have been adopted for
DDoS detection, the attack remains a major threat of the Internet. Most of the existing ML …

Abstract Distributed Denial of Service (DDoS) attack is transforming into a weapon by the
attackers, politicians, and cyber terrorists, etc. Today there is a quick ascent in the …

Software Defined Networking (SDN) centrally manages the network data layer to improve
the programmability and flexibility of networks by the controller. Because of centralized …

Abstract The Optical Burst Switching (OBS) network is mostly victimized to the Denial of
Service (DOS) attack, referred as Burst Header Packet (BHP) flooding attack can prevent …

DoS attack tools have become increasingly sophisticated challenging the existing detection
systems to continually improve their performances. In this paper we present a victimend DoS …