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Artificial neural networks (ANN) consider classification as one of the most dynamic research and application areas. ANN is the branch of Artificial Intelligence (AI). The neural network was trained by back propagation algorithm. The different combinations of functions and its effect while using ANN as a classifier is studied and the correctness of these functions are analyzed for various kinds of datasets. The back propagation neural network (BPNN) can be used as a highly successful tool for dataset classification with suitable combination of training, learning and transfer functions. When the maximum likelihood method was compared with backpropagation neural network method, the BPNN was more accurate than maximum likelihood method. A high predictive ability with stable and well functioning BPNN is possible. Multilayer feed-forward neural network algorithm is also used for classification. However BPNN proves to be more effective than other classification algorithms. KEYWORDSBack propagation algorithm, Maximum Likelihood method, Multilayer feed-forward neural network.

ABSTRACT

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Nowadays Information Security plays an important role in Hi-tech computing world. Even though firewall is used to provide security between two different networks, it fails to care about the intranet security (security within a single network). In order to overcome the problem a model called Intrusion Detection System is used. The process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). In this experiment, we investigated Decision trees algorithm. To train the soft computing techniques we are using the Benchmark KDD cup Data set.