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Cybernetic attacks have been increasingly common and cause great harm to people and organizations. Late detection of such attacks increases the possibility of irreparable damage, with high financial losses being a common occurrence. This article proposes TeMIA-NT (ThrEat Monitoring and Intelligent data Analytics of Network Traffic), a real-time flow analysis system that uses parallel flow processing. The main contributions of the TeMIA-NT are: i) the proposal of an architecture for realtime detection of network intrusions that supports high traffic rates, ii) the use of the structured streaming library, and iii) two modes of operation: offline and online. The offline operation mode allows evaluating the performance of multiple machine learning algorithms over a given dataset, including metrics such as accuracy, F1-score, and area under the curve (AUC). The proposal uses dataframe structures, in online mode, the …