Abstract
It is an important issue to detect the intrusion attacks for the security of network communication. The clustering-based methods usually are proposed to cope with the problem of intrusion detections. However, how to detect the unknown intrusion attacks within stream data has come to be a challenge. In this paper, we consider the intrusion attacks as outliers and propose a novel approach (called DOExMiCluster) based on clustering data stream to detect the outliers of unknown type. The new micro-cluster concept, normalization data technology and k-mean measure are only used to learn the normal sub micro-clusters online till the event that two special micro-clusters are merged and a new micro-cluster is created doesn’t appear, and then system recognizes the instances which cannot fall into any micro-clusters as outliers.
Published Version
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