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Information assurance and security has been a major issue of serious global concern in the wake of rapid expansion of computer systems. Intrusion Detection Systems (IDS) form a key part of system defence, where it identifies abnormal activities happening in a computer system. Different soft-computing based methods have been proposed in recent years for the development of intrusion detection systems. The proposed technique is a four step methodology of which, first step is to perform the Fuzzy C-means clustering. Then, neural network is trained, such that each of the data point is trained with the corresponding neural network associated with the cluster.
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