This Disrupting Operations of Illicit Supply Networks (D-ISN) project will enhance national public safety, health, and welfare by improving the understanding of drug and sex trafficking networks, detecting their operational patterns, and developing mechanisms to disrupt their activities. The trafficking of humans and illicit drugs are pervasive problems in the United States, with immeasurable negative impacts on healthcare, social services, and criminal justice infrastructures. Combating these problems entails multiple challenges due to the nature of trafficking operations, which include scattered data, multiple agents, adaptability of both the market and traffickers, and hidden operations. To tackle these challenges, this project integrates expertise from academia, domain experts, and law enforcement agencies. This is achieved through rigorous field work with detectives and survivors, and methods of analysis from social sciences, operations research, computer science, and information science. The research plan focuses on the U.S. Southwest, whose main urban areas have street prostitution tracks, robust online sex advertisement markets, and active gang and drug distribution networks. The structured data repository resulting from this project will be publicly available to the research community.

This project employs a multi-scale approach that analyzes and develops interventions at macro- and micro-levels, leveraging both qualitative and quantitative methods. The research plan includes an illicit network discovery component to construct illicit supply networks out of contextual data from interviews with survivors and detectives, police case records, and nonconventional databases. This will allow for the systematic documentation of victim movement, drug movement, financial activity, use of transportation hubs, and how these are interconnected. The macro-level analysis provides a methodology to characterize the interdependency between actors, locations, and financial instruments involved in the illicit network operation. The analysis distills complex interdependencies into analytically tractable logical relationships for the design of organizational, financial, and geographical strategies that can thwart illicit activities. The micro-level component supports the design of interventions from law enforcement and social service perspectives at a finer and tactical geographical scale. The project develops new mathematical programming models for the inference of trafficking hot routes, which are predicted, high-density trafficking routes. It also includes a game theoretical framework for the disruption of hot routes.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2021-01-01
Budget End
2025-12-31
Support Year
Fiscal Year
2020
Total Cost
$1,000,000
Indirect Cost
Name
Arizona State University
Department
Type
DUNS #
City
Tempe
State
AZ
Country
United States
Zip Code
85281