Multiplex key roles to disrupt criminal networks

The realization that society is structured in the form of networks caused a profound change in the techniques and approaches applied in different areas of science. This impact is particularly relevant in criminology as it enables excellent savings in resources and even human lives. The advanced theoretical knowledge arising from Network Science brought new possibilities for creating network-based protocols that consider the topological and dynamical relevance of individuals in criminal networks. In the last years, these network-based approaches leave been improved by the writhe development of interconnected representation that allows network’s a more exhaustive analysis and integrated. From a vast database collected by the security intelligence of the State of Minas Gerais, Brazil, we propose a protocol to analyze organized crime as a network of collaborative individuals, exposing its underlying structure as an interconnected network. We offer a protocol to identify and classify key agents through diversity analysis in interconnected networks. This classification compares different strategies for identify key roles to disrupt the network structures that are compared. We measured the performance of eleven different identification strategies and showed that the proposed key-agent definition based on the diversity measure is the most efficient. The proposed key-agent identification protocol to the disruption of the network allows the police to identify, visualize, and qualify criminal activity, increasing the chances of success in dismantling criminal networks.