A Novel Framework for DDoS Detectionin Huge Scale Networks, Thanksto QoS Features
This addresses DDoS threats for cloud service providers, but appears incremental as it builds on standard methods.
The paper tackles DDoS detection in large-scale cloud networks by proposing a hybrid protocol, achieving unspecified improvements in sensitivity and efficiency.
It is not been a long time since the advent of cloud-based technology. However, in this short period of timeseveral advantages and disadvantages have been emerged. This is a problem solving technology with some threats as well. These threats and potential damages are not only limited to the cloud-based technologies, but they have always been against computer network infrastructures. One of these examples is Distributed Denial-of-Service (DDoS) intrusion which is of course one of the most complex and the most dangerous types of attacks. The impact of this type of attack, due to its powerful nature, is much higher on cloud systems since in case of occurrence, the service providers lose their services completely as well as their reputationand loyal customers. This, apparently,can even lead to the collapse of the stock and other destructive consequences. On the other hand, due to the properties of cloud service providers including large-scale infrastructures, DDoS intrusion detection algorithms need high sensitivity, innovation, and general improvements. Traditional structures of DDoS attack detection algorithms are designed for small-scale networks or at most for application camps. Lack of efficient algorithm is seemingly apparentfor the large-scale networks. Therefore, in this context we utilize standardmethods as well as a proposed hybrid protocol which is more appropriate in connection with cloud structures in order to detect DDoS attacks