Detecting a DDOS attack and preventing it is a tedious task in a distributed network. This research proposes a Big Data-based DDOS attack detection and prevention based on the DDOS attack tool, THC-SSL and Weka. A live DDOS attack is generated with the help of the THC-SSL tool, and the machine learning Weka helps in producing the results for the NSL KDD train and test datasets in accordance with confusion matrix and accuracy. A comparison is made for the different models in the Weka machine learning tool which makes the task easier where Big Data is implemented in the Weka tool. The proposed detection algorithm described in this research achieves an accuracy of 98.5% respectively for the important features like flag and src_bytes.