Due to the growth of Information Systems, different types of electronic attacks are happening day by day. This leads to the security breach rising every day Therefore it is of utmost important to protect highly sensitive and private information by securing the data. An intrusion detection system (IDS) monitors network or system activities and for nasty activities produces reports to a management. It monitors network traffic and its suspicious behaviour against security. Different types of intrusion detection methodologies are available, but all the current IDS are not perfect. Now a day’s Data mining concepts are used in the area of research in intrusion detection implementation. This paper tries to forward an idea of modifying the traditional K- means algorithm using fuzzy concept to prepare a model of intrusion detection system. The experiments have been done on the KDD Cup 99 dataset.

IDS, Data mining, KDD Cup, Clustering, Fuzzy, False Positive

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