1
Master's student of computer software engineering, Faculty of Engineering and Engineering, Central Tehran Branch
2
Assistant Professor of Islamic Azad University, Central Tehran Branch
Abstract
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.
Hosseinzadeh Moghaddam, M., Javad Mirabedini, S., banirostam, T. (2017). A New Method for Intrusion Detection Using Genetic Algorithm and Neural Network. International Journal of Information, Security and Systems Management, 6(1), 656-662.
MLA
M.R. Hosseinzadeh Moghaddam; S. Javad Mirabedini; T. banirostam. "A New Method for Intrusion Detection Using Genetic Algorithm and Neural Network". International Journal of Information, Security and Systems Management, 6, 1, 2017, 656-662.
HARVARD
Hosseinzadeh Moghaddam, M., Javad Mirabedini, S., banirostam, T. (2017). 'A New Method for Intrusion Detection Using Genetic Algorithm and Neural Network', International Journal of Information, Security and Systems Management, 6(1), pp. 656-662.
VANCOUVER
Hosseinzadeh Moghaddam, M., Javad Mirabedini, S., banirostam, T. A New Method for Intrusion Detection Using Genetic Algorithm and Neural Network. International Journal of Information, Security and Systems Management, 2017; 6(1): 656-662.
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