@inproceedings{9e900f5198e74124bffbf74e57f59024,
title = "Constructing and analyzing criminal networks",
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.",
keywords = "Analysis, Community detection, Criminal networks, Cybercrime, Social graph",
author = "Hamed Sarvari and Ehab Abozinadah and Alex Mbaziira and Damon McCoy",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Computer Society's Security and Privacy Workshops, SPW 2014 ; Conference date: 17-05-2014 Through 18-05-2014",
year = "2014",
month = nov,
day = "13",
doi = "10.1109/SPW.2014.22",
language = "English (US)",
series = "Proceedings - IEEE Symposium on Security and Privacy",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "84--91",
booktitle = "Proceedings - 2014 IEEE Security and Privacy Workshops, SPW 2014",
}