A Machine Learning Approach for DDoS Prevention System in Cloud Computing Environment

Cloud computing is a novel and rapidly expanding way for the IT industry to expand its business using resources available on a pay-as-you-go basis. What if the server goes down due to cyber-attacks? It’s a tremendous loss for the company because every minute counts, and if the data is lost or misused, the ramifications are a major issue for the cloud service provider. As a result, we offered a solution in this paper that, if implemented in the real world, will be able to mitigate Distributed Denial of Service (DDoS) attacks in cloud environments. According to the design, we have trained three machine learning classification models, including random forest, support vector machine, and logistic regression, on a real-world dataset called CICDDoS2019 from the Canadian Institute for Cyber Security, so that the proposed algorithm can choose the best classifier from the three to prevent an attack based on the traffic rate.