Cluster ensemble for intrusion detection systems
Peng Zhou, Zhishu Li · 2010
The paper introduces cluster ensemble for intrusion detection systems. Intrusion detection is a hard problem which is studied by many researchers and is a research hot pot. The idea is that we use cluster ensemble to decide which net-event is normal or unnormal. In this paper there are three works presented. First, we state a hard cluster ensemble method. Second, the model of cluster ensemble for IDS is illustrated in detail. Third, some UCI datasets and KDD99 dataset are chosen for the experiments, and the results show that cluster ensemble for IDS is better than any single algorithm or model.