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• W2531239968 abstract "The number and impact of attack over the Internet have been continuously increasing in the last years, pushing the focus of many research activities into the development of effective techniques to promptly detect and identify anomalies in the network traffic. In this paper, we propose a performance comparison between two different histogram based anomaly detection methods, which use either the Euclidean distance or the entropy to measure the deviation from the normal behaviour. Such an analysis has been carried out taking into consideration different traffic features." @default.
• W2531239968 created "2016-10-21" @default.
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• W2531239968 date "2016-01-01" @default.
• W2531239968 modified "2023-09-26" @default.
• W2531239968 title "Statistical Network Anomaly Detection: An Experimental Study" @default.
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• W2531239968 doi "https://doi.org/10.1007/978-3-319-48021-3_2" @default.
• W2531239968 hasPublicationYear "2016" @default.
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