Deep learning model for distributed denial of service (DDoS) detection

Distributed Denial of Service (DDoS) Attacks Detection Mechanism

Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that p...

Detecting Distributed Denial of Service (DDoS) Attacks through Inductive Learning

As the complexity of Internet is scaled up, it is likely for the Internet resources to be exposed to Distributed Denial of Service (DDoS) flooding attacks on TCP-based Web servers. There has been a lot of related work which focuses on analyzing the pattern of the DDoS attacks to protect users from them. However, none of these studies takes all the flags within TCP header into account, nor do th...

A Method for Investigating Distributed Denial of Service (DDoS) Attacks

Prevention of Distributed Denial of Service (DDoS) attacks before they achieve their intrusive objectives is a critical problem in network security. This is because the attacks rapidly build up and flood the networks with disruptive packets that consume network bandwidth within a short range of timestamp. Consequently, network activities are suddenly shutdown and legitimate users that are prese...

Distributed Denial of Service Defense Attack Tradeoff Analysis (DDOS-DATA)

Detection Mechanism for Distributed Denial of Service (DDoS) Attack in Mobile Ad-hoc Networks

Mobile ad hoc networks are non-static networks which formed without any central point communication infrastructure. In addition to node mobility, a ad-hoc is defined by bounded resource constraints such as bandwidth, battery power, and storage space. In this network, the intermediate nodes play role of router which routed the packets to the terminal node. The security challenges in the networks...