Feature Selection Using Rough-DPSO in Anomaly Intrusion Detection
نویسندگان
چکیده
Most of the existing IDS use all the features in network packet to evaluate and look for known intrusion patterns. This data contains irrelevant and redundant features. Unfortunately, the drawback to this approach is a lengthy detection process. In real-time environment this may degrade the performance of an IDS. Thus, feature selection is required to address this issue. In this paper, we use wrapper approach where we integrate Rough Set and Particle Swarm to form a 2-tier structure of feature selection. Experimental results show that feature subset proposed by Rough-PSO gives better representation of data and they are robust.
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