Borderline smote algorithm and feature selection-based network anomalies detection strategy

HIGHLIGHTS

  • who: Yong Sun and collaborators from the School of Electrical Engineering and Automation, Wuhan University, Wuhan, China have published the article: Borderline SMOTE Algorithm and Feature Selection-Based Network Anomalies Detection Strategy, in the Journal: Energies 2022, 4751 of /2022/
  • what: The aim of this Article is to verify that the proposed method can effectively perform feature selection in the presence of multiple features. In this paper, network information attack detection is carried out based on the CICIDS2017 dataset. For the dichotomous problem, the authors propose to measure the classification performance based on the precision . . .

     

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