3D anomaly bar visualization for large-scale network

Tao Zhang, Qi Liao, Lei Shi

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

1 Scopus citations

Abstract

In this VAST challenge, log data coming from locations all over the Bank of Money facilities that contains close one million IP addresses. Since the geography of the data plays an important role for potential anomalies detection, we present a particular visualization solution based on Google Earth that can provide measure and deal with geo-spatial data. By mapping three important attributes, i.e., number of connections, policy status and activity flag, into 3D bars on top of physical locations (coordinates), anomaly distribution and trends can be efficiently visualized and analyzed. The general KML file generator can be extended for further analysis on other GIS systems.

Original languageEnglish
Title of host publicationIEEE Conference on Visual Analytics Science and Technology 2012, VAST 2012 - Proceedings
Pages291-292
Number of pages2
DOIs
StatePublished - 2012
Event2012 IEEE Conference on Visual Analytics Science and Technology, VAST 2012 - Seattle, WA, United States
Duration: Oct 14 2012Oct 19 2012

Publication series

NameIEEE Conference on Visual Analytics Science and Technology 2012, VAST 2012 - Proceedings

Conference

Conference2012 IEEE Conference on Visual Analytics Science and Technology, VAST 2012
Country/TerritoryUnited States
CitySeattle, WA
Period10/14/1210/19/12

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