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Protocol Type Based Intrusion Detection Using RBF Neural Network
Aslihan Ozkaya, Bekir Karlik
Pages - 90 - 99     |    Revised - 15-07-2012     |    Published - 10-08-2012
Volume - 3   Issue - 4    |    Publication Date - December 2012  Table of Contents
RBF network, Intrusion Detection, Network Security, KDD dataset
Intrusion detection systems (IDSs) are very important tools for providing information and computer security. In IDSs, the publicly available KDD’99, has been the most widely deployed data set used by researchers since 1999. Using a common data set has been provided to compare the results of different researches. The aim of this study is to find optimal methods of preprocessing the KDD’99 data set and employ the RBF learning algorithm to apply an Intrusion Detection System.
CITED BY (2)  
1 Shrivastava, A., Baghel, M., & Gupta, H. (2013). A Novel Hybrid Feature Selection and Intrusion Detection Based On PCNN and Support Vector Machine. International Journal of Computer Technology and Applications, 4(6), 922.
2 Shrivastava, A., Baghel, M., & Gupta, H. (2013). A Review of Intrusion Detection Technique by Soft Computing and Data Mining Approach. International Journal of Advanced Computer Research, 3(3), 224.
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Miss Aslihan Ozkaya
Mevlana University - Turkey
Professor Bekir Karlik
Mevlana University - Turkey