Federated databases and actionable intelligence: using social network analysis to disrupt transnational wildlife trafficking criminal networks

Abstract

Wildlife trafficking, a focus of organized transnational crime syndicates, is a threat to biodiversity. Such crime networks span beyond protected areas holding strongholds of species of interest such as African rhinos. Such networks extend over several countries and hence beyond the jurisdiction of any one law enforcement authority. We show how a federated database can overcome disjoint information kept in different databases. We also show how social network analyses can provide law enforcers with targeted responses that maximally disrupt a criminal network. We introduce an actionable intelligence report using social network measures that identifies key players and predicts player succession. Using a rhino case study we illustrate how such a report can be used to optimize enforcement operations.