A fast instance reduction algorithm for intrusion detection scenarios

We live in a world that is being driven by data. This leads to challenges of extracting and analyzing knowledge from large volumes An example such challenge intrusion detection. Intrusion detection data sets are characterized huge volumes, which affects the learning classifier. So there need reduce size training sets. Fortunately, inspection analysis available showed many instances very similar do not provide relevant information classification process. prompted look for possibilities use fast algorithm that, as much possible, removes while enforcing rate. In this work, new instance reduction presented. The proposed provides greater efficiency during stage, without significantly affecting efficacy task.