Classification and Mitigation of DDOS attacks Based on Self-Organizing Map and Support Vector Machine
Aditya Kumar Shukla, Ashish Sharma
Abstract
The advantage of using the cloud is that it can scale up and down in response to changing demand. It also provides an environment that can scale up and down immediately in response to changing demand. Consequently, significant DDoS protection is required in order to limit the effects of downtime induced by DDoS attacks on the organization. DDoS invasions are also comprehended as distributed denial of service (DDoS) attacks, are a sort of critical attack that threatens network availability. The fact that these assaults have become more complicated and continue to evolve at a rapid pace has made detecting and countering them a difficult undertaking. A discussion of the many known tactics for detecting DDoS is also included and compares and contrasts existing DDoS detection strategies are based on a variety of parameters, evaluate their advantages and disadvantages, and propose a SVM and Self-Organizing Map based model that could especially mitigate these invasions while also supplying an excellent alternative resolution to present detection problems, among other things.