  Recently, there has been an interest in improving the resources available in
Intrusion Detection System (IDS) techniques. In this sense, several studies
related to cybersecurity show that the environment invasions and information
kidnapping are increasingly recurrent and complex. The criticality of the
business involving operations in an environment using computing resources does
not allow the vulnerability of the information. Cybersecurity has taken on a
dimension within the universe of indispensable technology in corporations, and
the prevention of risks of invasions into the environment is dealt with daily
by Security teams. Thus, the main objective of the study was to investigate the
Ensemble Learning technique using the Stacking method, supported by the Support
Vector Machine (SVM) and k-Nearest Neighbour (kNN) algorithms aiming at an
optimization of the results for DDoS attack detection. For this, the Intrusion
Detection System concept was used with the application of the Data Mining and
Machine Learning Orange tool to obtain better results
