Cloud computing has increased apparent notoriety and acceptance over the past years. The expediency of this virtual technology accompanies the budgetary issue. One of the essential characteristics of cloud computing, which assistances in decreasing the financial associated issues of the of the cloud providers is the on-demand assessing model. Moreover, malicious users mostly focus on the economic practicality of the cloud customers, as a result, such malicious are proficient to influence the accessibility and availability of cloud facilitated services. These attacks are known as Distributed Denial of service attacks. In this work, we propose a novel methodology dependent on network flow analysis at the targeted side to distinguish and moderate the DDoS attacks against virtual services. Experiments were carried out by using real time datasets to assess the execution of the proposed methodology and the results recommend that our proposed method can identify and alleviate the DDoS attacks with agreeable precision and minimal overhead. © Springer Nature Singapore Pte Ltd. 2020.