节点文献
A Framework for an Adaptive Anomaly Detection System with Fuzzy Data Mining
【Abstract】 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.
【关键词】 intrusion detection;
anomaly detection;
fuzzy cluster;
unsupervised;
network security;
【Key words】 intrusion detection; anomaly detection; fuzzy cluster; unsupervised; network security;
【Key words】 intrusion detection; anomaly detection; fuzzy cluster; unsupervised; network security;
【基金】 Supported by the National Natural Science Foun-dation of China (60573101) ;the Natural Science Foundation ofShaanxi Province (2005f43)
- 【文献出处】 Wuhan University Journal of Natural Sciences ,武汉大学学报(自然科学版.英文版) , 编辑部邮箱 ,2006年06期
- 【分类号】TP393.08
- 【被引频次】1
- 【下载频次】26