Denial of service detection with hybrid fuzzy set based feed forward neural network

Authors:
Yong Wang;Dawu Gu;Mi Wen;Jianping Xu;Haming Li
Affiliations:
Department of Computers Science and Technolgy, Shanghai University of Electric Power, Shanghai, China;Department of Computers Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computers Science and Technolgy, Shanghai University of Electric Power, Shanghai, China;Department of Computers Science and Technolgy, Shanghai University of Electric Power, Shanghai, China;Department of Computers Science and Technolgy, Shanghai University of Electric Power, Shanghai, China
Venue:
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Year:
2010

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Abstract

The paper presents a Denial of Service (DoS) intrusion detection method with hybrid fuzzy set based feed forward neural network from KDD cup 99 records The data are pre-processed by fuzzy set, which transform record string attributes to double types and find the data record internal rules After data pre-process, about 60 percent of selected KDD 99 64633 records are selected for training and each 20 percent for validation and test in the neural network all the training, validation and test results show 99.6 percent correctly classified cases and only 0.4 percent misclassified cases The experiment results show that the design is effective.