ANALYZING THE COVARIANCE MATRIX APPROACH FOR DDOS HTTP ATTACK DETECTION IN CLOUD ENVIRONMENTS

Abstract

In order to detect Distributed Denial of Service (DDoS) HTTP attacks in cloud environments, this study investigates the potential benefits of combining the covariance matrix method with Multi- Attribute Decision Making (MADM) skills. Evaluating this approach across various cloud settings and thresholds, it delves into data gathering, preprocessing, and anomaly detection. Multivariate analysis and real-time detection are two benefits of the method, which make it worth the complexity. In order to improve its scalability and accuracy, we can better identify DDoS attacks in cloud systems by comprehending its advantages and disadvantages.