Detection of Accuracy for Intrusion Detection System Using Neural Network Classifier

Provided by: International Journal of Emerging Technology and Advanced Engineering (IJETAE)
Topic: Security
Format: PDF
In recent years, the security has become a critical part of any industrial and organizational information systems. The intrusion detection system is an effective approach to deal with the problems of networks and so different classifiers are used to detect the different kinds of attacks. In this paper, the performance of intrusion detection with various neural network classifiers is compared. In this proposed research there are five types of classifiers used. They are Feed Forward Neural Network (FFNN), Elman Neural Network (ENN), Generalized Regression Neural Network (GRNN), Probabilistic Neural Network (PNN) and Radial Basis Neural Network (RBNN). In this problem, the feature reduction techniques are used to a given KDD Cup 1999 dataset.

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