• English
  • Deutsch
  • Log In
    Password Login
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. NetCapVis: Web-based Progressive Visual Analytics for Network Packet Captures
 
  • Details
  • Full
Options
2019
Conference Paper
Titel

NetCapVis: Web-based Progressive Visual Analytics for Network Packet Captures

Abstract
Network traffic log data is a key data source for forensic analysis of cybersecurity incidents. Packet Captures (PCAPs) are the raw information directly gathered from the network device. As the bandwidth and connections to other hosts rise, this data becomes very large quickly. Malware analysts and administrators are using this data frequently for their analysis. However, the currently most used tool Wireshark is displaying the data as a table, making it difficult to get an overview and focus on the significant parts. Also, the process of loading large files into Wireshark takes time and has to be repeated each time the file is closed. We believe that this problem poses an optimal setting for a client-server infrastructure with a progressive visual analytics approach. The processing can be outsourced to the server while the client is progressively updated. In this paper we present NetCapVis, an web-based progressive visual analytics system where the user can upload PCAP files, set initial filters to reduce the data before uploading and then instantly interact with the data while the rest is progressively loaded into the visualizations.
Author(s)
Ulmer, Alex
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Sessler, David
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Kohlhammer, Jörn
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Hauptwerk
IEEE Symposium on Visualization for Cyber Security, VizSec 2019
Project(s)
ATHENE
Funder
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
Konferenz
Symposium on Visualization for Cyber Security (VizSec) 2019
DOI
10.1109/VizSec48167.2019.9161633
File(s)
N-599726.pdf (12.64 MB)
Language
English
google-scholar
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Tags
  • Lead Topic: Digitized Work

  • Research Line: Human computer interaction (HCI)

  • web applications

  • ATHENE

  • CRISP

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022