Comparative Study of Different Models before Feature Selection and AFTER Feature Selection for Intrusion Detection
Janmejay Pant, Bhaskar Pant, Amit Juyal · International Journal of Computer Applications · 2014
A network data set may contain a huge amount of data and processing this huge amount of data is one of the most challenges task for network based intrusion detection system (IDS).Normally these data contain lots of redundant and irrelevant features.Feature selection approaches are used to extract the relevant features from the original data to improve the efficiency or accuracy of IDS.In this paper an effective feature selection approaches are used for the NSL KDD data set.The performance of the used classifiers measure and compared with each other.