Visualizing graph dynamics and similarity for enterprise network security and management

Qi Liao, Aaron Striegel, Nitesh Chawla

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

24 Scopus citations

Abstract

Managing complex enterprise networks requires an understanding at a finer granularity than traditional network monitoring. The ability to correlate and visualize the dynamics and inter-relationships among various network components such as hosts, users, and applications is non-trivial. In this paper, we propose a visualization approach based on the hierarchical structure of similarity/difference visualization in the context of heterogeneous graphs. The concept of hierarchical visualization starts with the evolution of inter-graph states, adapts to the visualization of intra-graph clustering, and concludes with the visualization of similarity between individual nodes. Our visualization tool, ENAVis (Enterprise Network Activities Visualization), quantifies and presents these important changes and dynamics essential to network operators through a visually appealing and highly interactive manner. Through novel graph construction and transformation, such as network connectivity graphs, MDS graphs, bipartite graphs, and similarity graphs, we demonstrate how similarity/dynamics can be effectively visualized to provide insight with regards to network understanding.

Original languageEnglish
Title of host publicationVizSec 2010 - Proceedings of the 7th International Symposium on Visualization for Cyber Security
PublisherAssociation for Computing Machinery
Pages34-45
Number of pages12
ISBN (Print)9781450300131
DOIs
StatePublished - 2010
Event7th International Symposium on Visualization for Cyber Security, VizSec 2010 - Ottawa, ON, Canada
Duration: Sep 14 2010Sep 14 2010

Publication series

NameACM International Conference Proceeding Series

Conference

Conference7th International Symposium on Visualization for Cyber Security, VizSec 2010
Country/TerritoryCanada
CityOttawa, ON
Period09/14/1009/14/10

Keywords

  • enterprise networks
  • graphs
  • local context
  • policy assessment
  • security
  • visual graph data mining
  • visualization

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