Visualization of data cubes for anomaly detection in network traffic data streams
- 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.
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| Author: | Volker AhlersORCiDGND, Tim Laue, Nils Wellermann, Felix HeineORCiDGND |
|---|---|
| URN: | urn:nbn:de:bsz:960-opus4-21606 |
| DOI: | https://doi.org/10.25968/opus-2160 |
| DOI original: | https://doi.org/10.1109/IDAACS53288.2021.9660978 |
| ISBN: | 978-1-6654-2605-3 |
| ISSN: | 2770-4254 |
| Parent Title (English): | 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) |
| Publisher: | IEEE |
| Document Type: | Conference Proceeding |
| Language: | English |
| Year of Completion: | 2021 |
| Publishing Institution: | Hochschule Hannover |
| Release Date: | 2022/01/24 |
| Tag: | Datenwürfel Data Cubes; Information Visualization; Multidimensional Analysis; Network Security; User Interfaces |
| GND Keyword: | Computersicherheit; Rechnernetz; Benutzeroberfläche; Visualisierung |
| First Page: | 272 |
| Last Page: | 277 |
| Link to catalogue: | 1795490780 |
| Institutes: | Fakultät IV - Wirtschaft und Informatik |
| DDC classes: | 004 Informatik |
| Licence (German): |  Urheberrechtlich geschützt |
