Cloud computing shares a group of resources such as software, infrastructure, applications, and business as services [1]. Services like SaaS (software as a service), PaaS (platform as a service), and IaaS (infrastructure as a service) are provided by cloud computing and are utilized by numerous clients [3]. The corporate deploys their cloud workspace to Public, Private, and Hybrid cloud as per their requirement [4]. In recent times, cloud computing meets many concerns with data security and reliability due to its enormous demand. Cloud computing is unquestionably successful, but this success could be affected by issues regarding the risks associated with the model’s likely misuse to carry out illicit actions. One of the major barriers to the widespread use of cloud computing services is cloud security. A serious and unexpected cloud attack known as Distributed Denial of Service, or DDoS, is one of the security problems that currently plague the cloud computing environment. There is no apparent solution found to terminate the DDoS attack. The private cloud model incorporates software or programs needed for security issues, such as a firewall with lack of scalability and self-adaptability [9]. This study explains the private cloud environment setup that was used to simulate the cloud environment to find the real-time attacks of cloud computing. Then DDoS attacks are simulated in the cloud environment and logs are collected for the analyses process. The cloud environment is simulated using OpenStack cloud platform and the dataset was collected in this study with DDoS attack protocols. The collected dataset is analyzed with the MultiLayer Perceptron-ANN, AdaBoost and Random Forest ensemble algorithms to detect the DDoS attack.