A Novel Approach For Reduction of DDOS Attacks in Cloud Computing using Non-Parametric Hypothesis

Abstract

Cloud Computing is an innovative area of research in computer science, where a computer resource is delivered to the user, based on his demand. Due to the continuous evolution of Cloud computing, there has been an increased concern for a number of stakeholders about the data that is being stored in the cloud. The most vulnerable security issue in the cloud area is a Distributed Denial of Service (DDoS) attacker, which is one of the many cloud security problems. DDoS attackers, in particular, are a group of machines intent on disintegrating the services of current resources through the unnecessarily exhaustion of a single service. Furthermore, a large number of studies suggested that DDoS attacks were shifting their focus to cloud infrastructures and services. In the last decade, a variety of preventive measures for dealing with the effects of a DDoS assault on the cloud computing environment have been presented in the literature. In this paper, Through the potential advantages of inductive reasoning, the Kruskal Wallis Hypothesis Test-based Detection and Adaptive Load Balancing Scheme (KWHT-DDOS-ALBS) is contributed for effective detection of RoQ DDoS attacks, and the discrepancy in the pile of the cloud infrastructure is balanced through the adoption of the methodology. The suggested KWHT-DDOS-ALBS technique's simulation experiments revealed a superior detection rate and adaptive task scheduling rate of roughly 23% and 28%, respectively, as compared to the standard DDoS countermeasures under examination.