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Understanding multistage attacks by attack-track based visualization of heterogeneous event streams

  • SUNY Buffalo

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

26 Scopus citations

Abstract

In this paper, we present a method of handling the visualization of hetereogeneous event traffic that is generated by intrusion detection sensors, log files and other event sources on a computer network from the point of view of detecting multistage attack paths that are of importance. We perform aggregation and correlation of these events based on their semantic content to generate Attack Tracks that are displayed to the analyst in real-time. Our tool, called the Event Correlation for Cyber-Attack Recognition System (EC-CARS) enables the analyst to distinguish and separate an evolving multistage attack from the thousands of events generated on a network. We focus here on presenting the environment and framework for multistage attack detection using ECCARS along with screenshots that demonstrate its capabilities.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Workshop on Visualization for Computer Security, VizSEC'06. Co-located with the 13th ACM Conference on Computer and Communications Security, CCS'06
Pages1-5
Number of pages5
DOIs
StatePublished - 2006
Event3rd International Workshop on Visualization for Computer Security, VizSEC'06. Co-located with the 13th ACM Conference on Computer and Communications Security, CCS'06 - Alexandria, VA, United States
Duration: Nov 3 2006Nov 3 2006

Publication series

NameProceedings of the 3rd International Workshop on Visualization for Computer Security, VizSEC'06. Co-located with the 13th ACM Conference on Computer and Communications Security, CCS'06

Conference

Conference3rd International Workshop on Visualization for Computer Security, VizSEC'06. Co-located with the 13th ACM Conference on Computer and Communications Security, CCS'06
Country/TerritoryUnited States
CityAlexandria, VA
Period11/3/0611/3/06

Keywords

  • Attack tracks
  • Intrusion detection
  • Visualization

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