An interdependent network interdiction model for disrupting sex trafficking networks

Abstract

We map the organized sex trafficking networks (STNs) into a network flow model and develop an interdependent network interdiction model (NIM) to disrupt such networks. Our model considers the interdependence between the information and physical victim networks and reformulates the problem using duality theory. Our NIM provides a clear strategy for interdicting STNs. Namely, it determines when to monitor (i.e., gather information) or arrest the criminals to maximize the impact of the interdiction operation and cripple the network. We tested our NIM using three federally prosecuted sex trafficking cases in the United States of different sizes and structural properties: hybrid, international transactional, and Tenancingo models. Our experiments show promising results regarding the effectiveness of our NIM in all network types. In addition to that, we tested our model with an increasingly higher fraction of missing information to account for the inherently hidden nature of illicit networks. Our study provides analytical insight regarding (1) the importance of building the case prior to the arrests of criminals in illicit networks and (2) deploying a holistic strategy to improve interdiction and enhance the fight against sex trafficking.