National Science Foundation Grants

A New Multi-Layered Network Approach for Improving the Detection of Human Trafficking

This EArly-concept Grant for Exploratory Research (EAGER) will advance the national health and security by addressing the supply chains that allow human trafficking to function effectively. Human trafficking is one of the top revenue generators for illicit traders and has devastating effects on its victims, many of which are U.S. citizens. By aiding the detection and disruption of the social, financial, and physical networks used by criminal organizations that traffic individuals, this research will help to limit their operations and funding, thereby enhancing national security. Combating human trafficking will also have a positive impact on the lives of many youth, particularly females. The research outcomes will significantly advance the state of the art in social science and operations research. Insights from the research will be included in classes on operations research, human trafficking, illicit trade and transnational crime included in the programs of both the Schar School of Policy and Government and the Volgenau School of Engineering at George Mason University.

This research will use a multi-layered network approach that provides a systematic way to incorporate different types of data sources and multidisciplinary models into a holistic approach. The project combines social science methods with operations research methods to develop quantitative models that describe the complex operations of trafficking networks. The first phase will include analysis of existing and available data on human trafficking supply chains, transport logistics and financial transactions. To improve the detection of human trafficking, a new paradigm that enables the analysis of these multiple overlapping networks will be developed. The analysis of data on available human trafficking cases will be published on the website of the Transnational Crime and Corruption Center at George Mason University and widely disseminated within the larger community of government, business and policy makers concerned with supply chains, human trafficking and illicit trade.

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.

Principal Investigator: Louise Shelley

Co-Principal Investigator: Edward Huang


Collaborative Research: An Interdisciplinary Approach to Understanding, Modeling, and Disrupting Drug and Counterfeit Illicit Supply Chains

The objective of this five-year Disrupting Operations of Illicit Supply Networks (D-ISN) study is to understand the operations of illicit actors in the cyberworld, in both the open web and dark web, and the supply chains and payment systems for online drug sales, counterfeit pharmaceuticals, and goods, including Personal Protective Equipment (PPE). It seeks to catalyze game-changing technological innovations by creating tools and supply chain models to improve discovery and traceability of illicitly sourced products and identify effective disruption strategies. These supply chains will be studied from source to delivery through the money laundering of profits. The results will be informed by datasets drawn from open and dark websites and from data made available by industrial collaborators. The project will advance our national ability to counter malicious activities in the cyberworld and social media innovative approaches using mathematical models, supply chain analytics and computer science for the detection and disruption of drug and counterfeit supply chains.

The project uses a multidisciplinary set of methods which include data analysis, mathematical modeling, and ethnographic approaches to advance our understanding of online drug and counterfeit supply chains and how to disrupt them. Specially, this project will address three major goals in combating drug and counterfeit illicit supply chains: (1) understanding and detecting the illicit trade patterns quantitatively and qualitatively by using data from the payment processing, hosting, underground communications and court cases; (2) constructing a description of the supply chain that can then be modeled using appropriate techniques such as non-cooperative game theory framework to study different disruption strategies; and (3) studying the possibility of different disruption strategies that could be implemented by government, corporate and multilateral actors. The project will integrate advanced automated data collection and analysis tools, and sociological analysis of the illicit trafficking networks, and adversarial game theory frameworks. The project team’s collaboration with industry and discussions with law enforcement agencies will facilitate an interactive process that can fine-tune disruption techniques and suggest pragmatic real-world implementation strategies and policy recommendations.

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.

Principal Investigator: Louise Shelley

Co-Principal Investigator: Edward Huang