Title Of Paper:
 
 
A Combination of SVM, Neural Network and Decision Tree in Intrusion Detection Systems
Author's Name :  Saba Sedigh Rad, Farzad Galavandi , Asiye mirdoraghi
KeyWords:  Intrusion detection system, MLP neural networks, KNN, SVM.
Pages:  28 -35
Volume: 3
Issue: 3
Year: 2015
Abstract:
 

Computerized networks are considered as an integral part of our mechanized life, so network security against possible risks is of great importance. In order to create network security, software techniques were developed, which are referred to as intrusion detection system. The aim of intrusion detection system is to detect any illegal availability, sabotage and damage to computer systems and networks by both inner users and out intruders. In the present study, an approach combined of SVM algorithms, MLP neural networks and decision tree is presented to design the intrusion detection system. The proposed strategy is examined through the dataset KDDCup99. The results indicate an optimal rate of accuracy and precision in detection compared to other detective approaches.

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