Visualization of Data Cubes for Anomaly Detection in Network Traffic Data Streams
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| Title: | Visualization of Data Cubes for Anomaly Detection in Network Traffic Data Streams |
|---|---|
| Authors: | Ahlers, Volker, Laue, Tim, Wellermann, Nils, Heine, Felix |
| Source: | 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). :272-277 |
| Publisher Information: | IEEE, 2021. |
| Publication Year: | 2021 |
| Subject Terms: | Computersicherheit, Rechnernetz, Benutzeroberfläche, ddc:004, Visualisierung, 004 Informatik |
| Description: | For anomaly-based intrusion detection in computer networks, data cubes can be used for building a model of the normal behavior of each cell. During inference an anomaly score is calculated based on the deviation of cell metrics from the corresponding normality model. A visualization approach is shown that combines different types of diagrams and charts with linked user interaction for filtering of data. |
| Document Type: | Article Conference object |
| File Description: | application/pdf |
| DOI: | 10.1109/idaacs53288.2021.9660978 |
| DOI: | 10.25968/opus-2160 |
| Access URL: | https://serwiss.bib.hs-hannover.de/files/2160/ahlers_idaacs_2021.pdf |
| Rights: | IEEE Copyright "In Copyright" Rights Statement |
| Accession Number: | edsair.doi.dedup.....d1b5cfc74a3f15494cc62aef5661d922 |
| Database: | OpenAIRE |
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