A review on Attribute Selection for Intrusion Detection System with Evolutionary Algorithm

The process of clustering technique plays an important role in intrusion detection system. The processes of clustering technique grouped the network traffic data on the basis of similarity and validate the traffic data. The process of clustering suffered from the problem of large number of iteration and loss of data. Now a day’s various authors used various optimization technique for the controlling the number of iteration and selection of seed. In this paper present review of intrusion detection techniques for clustering data using KDDCUP dataset which include both normal and abnormal data.

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