Proactive Detection of DDoS Attacks Utilizing k-NN Classifier in an Anti-DDos Framework

Distributed Denial-of-Service (DDoS) attacks pose a serious threat to network security. There have been a lot of methodologies and tools devised to detect DDoS attacks and reduce the damage they cause. Still, most of the methods cannot simultaneously achieve efficient detection with a small number of false alarms and real-time transfer of packets. Here, the authors introduce a method for proactive detection of DDoS attacks, by classifying the network status, to be utilized in the detection stage of the proposed anti-DDoS framework. Initially, they analyse the DDoS architecture and obtain details of its phases. Then, they investigate the procedures of DDoS attacks and select variables based on these features.