Visible to the public GIS mapping and spatial analysis of cybersecurity attacks on a florida university

TitleGIS mapping and spatial analysis of cybersecurity attacks on a florida university
Publication TypeConference Paper
Year of Publication2015
AuthorsHu, Zhiyong, Baynard, C. W., Hu, Hongda, Fazio, M.
Conference Name2015 23rd International Conference on Geoinformatics
Date Publishedjun
Keywordsadvanced spatial statistical analysis functions, Computer crime, cyber-attack detection, cyberattack, cybersecurity, cybersecurity attacks, cybersecurity threat detection software, Data analysis, data visualisation, Data visualization, educational administrative data processing, Educational institutions, exploratory spatial data analysis, GEO-IP software, Geographic Information System (GIS), geographic information systems, geographic Internet protocol software, GIS mapping, Grippers, point pattern analysis, pubcrawl170109, R software, security of data, Software, Spatial analysis, spatial point pattern analysis, spatial statistics, statistical analysis, statistical models, University of North Florida, US universities, visualization
Abstract

As the centers of knowledge, discovery, and intellectual exploration, US universities provide appealing cybersecurity targets. Cyberattack origin patterns and relationships are not evident until data is visualized in maps and tested with statistical models. The current cybersecurity threat detection software utilized by University of North Florida's IT department records large amounts of attacks and attempted intrusions by the minute. This paper presents GIS mapping and spatial analysis of cybersecurity attacks on UNF. First, locations of cyberattack origins were detected by geographic Internet Protocol (GEO-IP) software. Second, GIS was used to map the cyberattack origin locations. Third, we used advanced spatial statistical analysis functions (exploratory spatial data analysis and spatial point pattern analysis) and R software to explore cyberattack patterns. The spatial perspective we promote is novel because there are few studies employing location analytics and spatial statistics in cyber-attack detection and prevention research.

DOI10.1109/GEOINFORMATICS.2015.7378714
Citation Keyhu_gis_2015