A New Method for Intrusion Detection Using Genetic Algorithm and Neural Network

نویسندگان

  • M.R. Hosseinzadeh Moghaddam Master's student of computer software engineering, Faculty of Engineering and Engineering, Central Tehran Branch
  • S. Javad Mirabedini Assistant Professor of Islamic Azad University, Central Tehran Branch
  • T. banirostam Assistant Professor of Islamic Azad University, Central Tehran Branch
چکیده مقاله:

    The article attempts to have neural network and genetic algorithm techniques present a model for classification on dataset. The goal is design model can the subject acted a firewall in network and this model with compound optimized algorithms create reliability and accuracy and reduce error rate couse of this is article use feedback neural network and compared to previous methods increase accuracy classification rate and reduce error rate. The proposed method increased with simulation accuracy of 99.97 percent.

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عنوان ژورنال

دوره 6  شماره 1

صفحات  656- 662

تاریخ انتشار 2017-06-01

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