Yeni bir saldırı tespit sistemi geliştirmek için yeni bir yöntem

After the increased use of digital devices connected to the Internet, which in turn leads to users sharing their personal information, the adoption of intergovernmental institutions, including civil ones, in their work of archiving, management, marketing, etc. . On networked distributed systems, security experts have made the focus of their efforts to provide the necessary cybersecurity, which is to prevent interference by unauthorized persons from gaining access to databases and to protect networks from malicious attacks that cause losses of funds or assets connected to digital networks. Network and in our research, we tried to address the problem of (DDoS) through machine learning technology, where the (Extra Trees Classifier) algorithm was used, which reduces the size of the input data with a low computational cost and low variance, and the Random Forest algorithm with a low bias to choose the best available results from the ExtraTreesClassifier and train The model using the (Dense Neural Network) for learning and testing (IDS) model achieved an accuracy of 99.85%.