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A Framework for an Adaptive Anomaly Detection System with Fuzzy Data Mining

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【Author】 GAO Xiang, WANG Min, ZHAO Rongchun School of Computer, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China

【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.

【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
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