@inproceedings{AhlersLaueWellermannetal.2021,
  author    = {Volker Ahlers and Tim Laue and Nils Wellermann and Felix Heine},
  title     = {Visualization of data cubes for anomaly detection in network traffic data streams},
  series = {2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)},
  publisher = {IEEE},
  isbn      = {978-1-6654-2605-3},
  issn      = {2770-4254},
  doi       = {10.25968/opus-2160},
  url       = {http://nbn-resolving.de/urn:nbn:de:bsz:960-opus4-21606},
  pages     = {272 -- 277},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}