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A Framework for an Adaptive Anomaly Detection System with Fuzzy Data Mining 被引量:1

A Framework for an Adaptive Anomaly Detection System with Fuzzy Data Mining
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摘要 In this paper, we present an adaptive anomaly detection framework that isapplicable 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. In this paper, we present an adaptive anomaly detection framework that isapplicable 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.
机构地区 School of Computer
出处 《Wuhan University Journal of Natural Sciences》 CAS 2006年第6期1797-1800,共4页 武汉大学学报(自然科学英文版)
基金 Supported by the National Natural Science Foun-dation of China (60573101) the Natural Science Foundation ofShaanxi Province (2005f43)
关键词 intrusion detection anomaly detection fuzzy cluster UNSUPERVISED network security intrusion detection anomaly detection fuzzy cluster unsupervised network security
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参考文献10

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