Virtual Red Light Districts: Detecting Covert Networks and Sex Trafficking Circuits in the U.S

Abstract

The United States is the second leading destination country for sex trafficking in the world. Increased effort to understand patterns of sex trafficking within the U.S. is imperative to combatting this issue. Covert networks are increasingly using information and communication technologies (ICTs) to extend their operations. Due to the increase in sex trafficking network activity online, there is a need for systematic research and methods especially in terms of technology facilitated sex trafficking. This study examined how publicly available information can be used to uncover covert networks and sex trafficking patterns in the United States through the study of dark networks from a sociotechnical perspective. The intent was to observe the types of data available in online escort advertisements and to identify ways to exploit data into meaningful information that can be used to disrupt this activity. Network analysis methods were applied to sex trafficking activity in online environments to identify sex trafficking trends within the U.S. Content analysis was used to identify important data fields in online escort advertisement that presented virtual indicators of sex trafficking. This data was further exploited using social network analysis (SNA) methods to identify provider networks and movement trends. Methods are presented to identify potential victims, provider networks, and domestic movement trends. Covert networks are continuously balancing security risk with operational necessity to communicate to external audiences. By using the Internet as a communication channel it becomes a lens to observe this activity. Consistency of findings with known trafficking trends demonstrated the effectiveness of the method to uncover covert networks and circuits within the U.S.