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- W2170210941 abstract "During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks. However, having a relatively high false alarm rate, anomaly detection has not been wildly used in real networks. In this paper, we have proposed a novel anomaly detection scheme using the correlation information contained in groups of network traffic samples. Our experimental results show promising detection rates while maintaining false positives at very low rates." @default.
- W2170210941 created "2016-06-24" @default.
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- W2170210941 date "2008-05-01" @default.
- W2170210941 modified "2023-10-18" @default.
- W2170210941 title "A Novel Covariance Matrix Based Approach for Detecting Network Anomalies" @default.
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- W2170210941 doi "https://doi.org/10.1109/cnsr.2008.80" @default.
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