Sebastian Peryt, J. Morales, W. Casey, A. Volkmann, B. Mishra, Yang Cai
{"title":"可视化恶意软件分发网络","authors":"Sebastian Peryt, J. Morales, W. Casey, A. Volkmann, B. Mishra, Yang Cai","doi":"10.1109/VIZSEC.2016.7739585","DOIUrl":null,"url":null,"abstract":"In this paper, we present a case study of visual analytics of a Malware Distribution Network (MDN), a connected set of maliciously compromised domains used to disseminate malicious software to victimize computers and users. We formally define the graph of an MDN to visualize top-level-domain (TLD) data collected from Google Safe Browsing reports in a temporal manner characterizing the topological structure. From the collected data, we were able to identify and label a TLD's role in malware distribution. The visual analytics provided insights on the topological structure of MDNs over time including highly connected and persistent TLDs and subnetworks.","PeriodicalId":307308,"journal":{"name":"2016 IEEE Symposium on Visualization for Cyber Security (VizSec)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Visualizing a Malware Distribution Network\",\"authors\":\"Sebastian Peryt, J. Morales, W. Casey, A. Volkmann, B. Mishra, Yang Cai\",\"doi\":\"10.1109/VIZSEC.2016.7739585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a case study of visual analytics of a Malware Distribution Network (MDN), a connected set of maliciously compromised domains used to disseminate malicious software to victimize computers and users. We formally define the graph of an MDN to visualize top-level-domain (TLD) data collected from Google Safe Browsing reports in a temporal manner characterizing the topological structure. From the collected data, we were able to identify and label a TLD's role in malware distribution. The visual analytics provided insights on the topological structure of MDNs over time including highly connected and persistent TLDs and subnetworks.\",\"PeriodicalId\":307308,\"journal\":{\"name\":\"2016 IEEE Symposium on Visualization for Cyber Security (VizSec)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Symposium on Visualization for Cyber Security (VizSec)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VIZSEC.2016.7739585\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Symposium on Visualization for Cyber Security (VizSec)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VIZSEC.2016.7739585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we present a case study of visual analytics of a Malware Distribution Network (MDN), a connected set of maliciously compromised domains used to disseminate malicious software to victimize computers and users. We formally define the graph of an MDN to visualize top-level-domain (TLD) data collected from Google Safe Browsing reports in a temporal manner characterizing the topological structure. From the collected data, we were able to identify and label a TLD's role in malware distribution. The visual analytics provided insights on the topological structure of MDNs over time including highly connected and persistent TLDs and subnetworks.