A New Method for Intrusion Detection Using Genetic Algorithm and Neural Network
الموضوعات : International Journal of Information, Security and Systems Management
M.R. Hosseinzadeh Moghaddam
1
(Master's student of computer software engineering, Faculty of Engineering and Engineering, Central Tehran Branch)
S. Javad Mirabedini
2
(Assistant Professor of Islamic Azad University, Central Tehran Branch)
T. banirostam
3
(Assistant Professor of Islamic Azad University, Central Tehran Branch)
الکلمات المفتاحية: Genetic algorithm, Neural Network, Intrusion Detection System, Clustring and Gravitational Search Algorithm,
ملخص المقالة :
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.
