Cascaded intrusion detection using an improved clustering method
Zhen Bao, Di He · 2009
An improved clustering method used for cascaded intrusion detection is proposed in this paper. It can detect different kinds of intrusions by arranging the processing framework in a cascaded way, based on which we can abstract corresponding features to achieve clustering. Computer simulations based on the 1999 KDD CUP dataset show the effectiveness of the proposed approach in detecting various intrusions and superiority to other clustering methods.