Hamed Sarvari, Ehab A. Abozinadah, Alex V. Mbaziira, Damon McCoy
{"title":"构建和分析犯罪网络","authors":"Hamed Sarvari, Ehab A. Abozinadah, Alex V. Mbaziira, Damon McCoy","doi":"10.1109/SPW.2014.22","DOIUrl":null,"url":null,"abstract":"Analysis of criminal social graph structures can enable us to gain valuable insights into how these communities are organized. Such as, how large scale and centralized these criminal communities are currently? While these types of analysis have been completed in the past, we wanted to explore how to construct a large scale social graph from a smaller set of leaked data that included only the criminal's email addresses. We begin our analysis by constructing a 43 thousand node social graph from one thousand publicly leaked criminals' email addresses. This is done by locating Facebook profiles that are linked to these same email addresses and scraping the public social graph from these profiles. We then perform a large scale analysis of this social graph to identify profiles of high rank criminals, criminal organizations and large scale communities of criminals. Finally, we perform a manual analysis of these profiles that results in the identification of many criminally focused public groups on Facebook. This analysis demonstrates the amount of information that can be gathered by using limited data leaks.","PeriodicalId":142224,"journal":{"name":"2014 IEEE Security and Privacy Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"57","resultStr":"{\"title\":\"Constructing and Analyzing Criminal Networks\",\"authors\":\"Hamed Sarvari, Ehab A. Abozinadah, Alex V. Mbaziira, Damon McCoy\",\"doi\":\"10.1109/SPW.2014.22\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analysis of criminal social graph structures can enable us to gain valuable insights into how these communities are organized. Such as, how large scale and centralized these criminal communities are currently? While these types of analysis have been completed in the past, we wanted to explore how to construct a large scale social graph from a smaller set of leaked data that included only the criminal's email addresses. We begin our analysis by constructing a 43 thousand node social graph from one thousand publicly leaked criminals' email addresses. This is done by locating Facebook profiles that are linked to these same email addresses and scraping the public social graph from these profiles. We then perform a large scale analysis of this social graph to identify profiles of high rank criminals, criminal organizations and large scale communities of criminals. Finally, we perform a manual analysis of these profiles that results in the identification of many criminally focused public groups on Facebook. This analysis demonstrates the amount of information that can be gathered by using limited data leaks.\",\"PeriodicalId\":142224,\"journal\":{\"name\":\"2014 IEEE Security and Privacy Workshops\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"57\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Security and Privacy Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPW.2014.22\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Security and Privacy Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPW.2014.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of criminal social graph structures can enable us to gain valuable insights into how these communities are organized. Such as, how large scale and centralized these criminal communities are currently? While these types of analysis have been completed in the past, we wanted to explore how to construct a large scale social graph from a smaller set of leaked data that included only the criminal's email addresses. We begin our analysis by constructing a 43 thousand node social graph from one thousand publicly leaked criminals' email addresses. This is done by locating Facebook profiles that are linked to these same email addresses and scraping the public social graph from these profiles. We then perform a large scale analysis of this social graph to identify profiles of high rank criminals, criminal organizations and large scale communities of criminals. Finally, we perform a manual analysis of these profiles that results in the identification of many criminally focused public groups on Facebook. This analysis demonstrates the amount of information that can be gathered by using limited data leaks.