DocumentCode :
154240
Title :
Constructing and Analyzing Criminal Networks
Author :
Sarvari, Hamed ; Abozinadah, Ehab ; Mbaziira, Alex ; Mccoy, Damon
fYear :
2014
fDate :
17-18 May 2014
Firstpage :
84
Lastpage :
91
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 :
graph theory; social networking (online); unsolicited e-mail; Facebook profiles; criminal network analysis; criminal network construction; criminal organizations; criminally-focused public group identification; data leakage; high-rank criminal profiles; large-scale centralized criminal communities; large-scale criminal social graph structure analysis; public social graph; publicly leaked criminal e-mail addresses; social graph node; Communities; Electronic mail; Facebook; Joining processes; Manuals; Organizations; analysis; community detection; criminal networks; cybercrime; social graph;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Security and Privacy Workshops (SPW), 2014 IEEE
Conference_Location :
San Jose, CA
Type :
conf
DOI :
10.1109/SPW.2014.22
Filename :
6957290
Link To Document :
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