A Deep and Efficient Analysis of DDOS Attack in Software Defined Network

Abstract

DDoS assaults are one of the most serious issues that the Internet has to deal with. Various defense strategies have been offered to remove this form of assault, the number of which has risen over the research period. However, no detection method capable of entirely thwarting the assaults has yet been discovered. As a result, computer security experts must be vigilant in detecting and defending against DDoS assaults. This study gives a comprehensive assessment of the scholarly literature on DDoS attack detection strategies. The key components of detection have been defined based on the literature. Methods, variables, tools-kits, positioning site, point in time, and detection precision were recognized as four factors for examination in this inquiry. It was discovered that each strategy for detecting assaults takes use of certain aspects of network load, user requirements, and specialized kits. Finally, it was able to pinpoint the mechanisms with the greatest impact. The datasets they utilize, for example, can affect detection accuracy. It's been determined that a thorough examination of the aforementioned components of DDoS attack detection underwrite the development of an adequate approach for Defending against the attacks. These approaches bank on better router functionality or fluctuations to present protocols. The pros and cons of current research approaches in this issue are also describe.