A framework for an adaptive anomaly detection system with fuzzy data mining
Xiang Gao, Min Wang, Zhao Rongchun · Wuhan University Journal of Natural Sciences · 2006
In this paper, we present an adaptive anomaly detection framework that is applicable to network-based intrusion detection. Our framework employs fuzzy cluster algorithm to detect anomalies in an online, adaptive fashion without a priori knowledge of the underlying data. We evaluate our method by performing experiments over network records from the KDD CUP99 data set.