The key success factor of the business depends upon correct and timely information. The vital resources of the organization should be protected from inside and outside threats. Among many threats of network security, intrusion has become a crucial reason for many organizations to incur loss. Many researchers are trying their level best to handle the different types of intrusion affecting the business. To detect such a type of intrusion, our initiative is to us a very popular soft computing tool namely back propagation neural network (BPNN). We have prepared a flexible BPNN architecture to identify the intrusion with the help of anomaly detection methodology. The result we obtained is better than or at per with many best research paper in this field of study. We have used KDD dataset for our experiment.

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