Volltext-Downloads (blau) und Frontdoor-Views (grau)

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.

Download full text files

  • Volltexteng

    © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Export metadata

Additional Services

Share in Twitter Search Google Scholar


Author:Volker AhlersORCiDGND, Tim Laue, Nils Wellermann, Felix HeineORCiDGND
DOI original:https://doi.org/10.1109/IDAACS53288.2021.9660978
Parent Title (English):2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)
Document Type:Conference Proceeding
Year of Completion:2021
Publishing Institution:Hochschule Hannover
Release Date:2022/01/24
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):License LogoUrheberrechtlich geschützt