Biblio

Distributed Denial of Service (DDoS) attacks are one of the most important threads in network systems. Due to the distributed nature, DDoS attacks are very hard to detect, while they also have the destructive potential of classical denial of service attacks. In this study, a novel 2-step system is proposed for the detection of DDoS attacks. In the first step an anomaly detection is performed on the destination IP traffic. If an anomaly is detected on the network, the system proceeds into the second step where a decision on every user is made due to the behaviour models. Hence, it is possible to detect attacks in the network that diverges from users' behavior model.

Cloud computing has emerged as an increasingly popular means of delivering IT-enabled business services and a potential technology resource choice for many private and government organizations in today's rapidly changing computing environment. Consequently, as cloud computing technology, functionality and usability expands unique security vulnerabilities and treats requiring timely attention arise continuously. The primary challenge being providing continuous service availability. This paper will address cloud security vulnerability issues, the threats propagated by a distributed denial of service (DDOS) attack on cloud computing infrastructure and also discuss the means and techniques that could detect and prevent the attacks.