{"title":"佛罗里达大学网络安全攻击的GIS制图和空间分析","authors":"Zhiyong Hu, Chris W. Baynard, Hongda Hu, M. Fazio","doi":"10.1109/GEOINFORMATICS.2015.7378714","DOIUrl":null,"url":null,"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.","PeriodicalId":371399,"journal":{"name":"2015 23rd International Conference on Geoinformatics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"GIS mapping and spatial analysis of cybersecurity attacks on a florida university\",\"authors\":\"Zhiyong Hu, Chris W. Baynard, Hongda Hu, M. Fazio\",\"doi\":\"10.1109/GEOINFORMATICS.2015.7378714\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":371399,\"journal\":{\"name\":\"2015 23rd International Conference on Geoinformatics\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 23rd International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GEOINFORMATICS.2015.7378714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 23rd International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEOINFORMATICS.2015.7378714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GIS mapping and spatial analysis of cybersecurity attacks on a florida university
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.