Anomaly classi cation using genetic algorithm-based random forest model for network attack detection

HIGHLIGHTS

• who: KDD and collaborators from the Management Information Systems Department, College of Business, King Khalid University, Abha, Saudi Arabia have published the research work: Anomaly Classi cation Using Genetic Algorithm-Based Random Forest Model for Network Attack Detection, in the Journal: (JOURNAL)
• what: The authors propose to use the genetic algorithm (GA) for selecting the appropriate values of these two parameters optimizing the RF classifier and improving the classification accuracy of normal and abnormal network traffics. The work introduced by Solanki et_al has computed the accuracy of decision tree (C4.5) and support vector machine . . .
  

   

  

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