Hierarchical Adaptive FCM To Detect Attacks Using Layered Approach

In this modern world, computer has been used as a tool for crime. Because of this kind of hacking,companies are getting loss.By using intrusion detection system(IDS), the attacks can be detected and that can be corrected. We also check the effectiveness and ineffectiveness in finding the anomalies by considering the network data.Intrusion detection system (IDS) provides a layer that monitors the network traffic for predefined suspicious patterns and inform about the misactivity. In this paper, we address the clustering methods and the method for detecting attacks. Experiments performed on the KDD CUP 1999 Dataset. We address for 5 categories of attacks like back attacks,Neptune attacks,smurf attacks,warezclient attacks and ipsweep attacks. Fuzzy C-Means clustering is used to train the network data. Hierarchical FCM is used for further classification.