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Recently, there has been an interest in improving the resources available inIntrusion Detection System (IDS) techniques. In this sense, several studiesrelated to cybersecurity show that the environment invasions and informationkidnapping are increasingly recurrent and complex. The criticality of thebusiness involving operations in an environment using computing resources doesnot allow the vulnerability of the information. Cybersecurity has taken on adimension within the universe of indispensable technology in corporations, andthe prevention of risks of invasions into the environment is dealt with dailyby Security teams. Thus, the main objective of the study was to investigate theEnsemble Learning technique using the Stacking method, supported by the SupportVector Machine (SVM) and k-Nearest Neighbour (kNN) algorithms aiming at anoptimization of the results for DDoS attack detection. For this, the IntrusionDetection System concept was used with the application of the Data Mining andMachine Learning Orange tool to obtain better results

Ensemble learning techniques for intrusion detection system in the context of cybersecurity