A Regression Model to Secure Cloud Datacenter Against DDoS Attack

Cloud computing is a major area for conventional IT executions since it offers insignificant expense and admittance to “pay-as-you-go” registering capacities and concerning requests by clients. The cloud offers systems, stages, and software through cloud climate models. There are numerous security-related issues in this domain. A distributed denial of service (DDoS) attack can be named a “ tsunami ” due to its devastating effect. DDoS attacks are a ceaseless danger to present-day organizations, causing serious business fiascos, client issues, and monetary misfortunes. This study utilizes a machine learning strategy named the Logistic Regression model to give security to servers working in a cloud climate against DDoS. This assists with giving security and is valuable in updating the strong advancement of associations. WEKA tool is used to develop a regression model. The data set used is NSL-KDD. The model helped categorize traffic as normal or anomaly with high accuracy and precision.