The web of federal crimes in Brazil: topology, weaknesses, and control
Law enforcement and intelligence agencies worldwide struggle to find effective ways to fight and control organized crime. However, illegal networks operate outside the law and much of the data collected is classified. Therefore, little is known about criminal networks structure, topological weakness...
| Authors: | ; |
|---|---|
| Format: | Electronic Article |
| Language: | English |
| Published: |
2017
|
| In: |
Applied network science
Year: 2017 |
| Online Access: |
Volltext (kostenfrei) Volltext (kostenfrei) |
| Journals Online & Print: | Drawer...
|
| Check availability: | HBZ Gateway |
| Keywords: |
| Summary: | Law enforcement and intelligence agencies worldwide struggle to find effective ways to fight and control organized crime. However, illegal networks operate outside the law and much of the data collected is classified. Therefore, little is known about criminal networks structure, topological weaknesses, and control. In this contribution we present a unique criminal network of federal crimes in Brazil. We study its structure, its response to different attack strategies, and its controllability. Surprisingly, the network composed of multiple crimes of federal jurisdiction has a giant component, enclosing more than a half of all its edges. This component shows some typical social network characteristics, such as small-worldness and high clustering coefficient, however it is much "darker" than common social networks, having low levels of edge density and network efficiency. On the other side, it has a very high modularity value, $Q=0.96$. Comparing multiple attack strategies, we show that it is possible to disrupt the giant component of the network by removing only $2\%$ of its edges or nodes, according to a module-based prescription, precisely due to its high modularity. Finally, we show that the component is controllable, in the sense of the exact network control theory, by getting access to $20\%$ of the driver nodes.Comment: 9 pages, 5 figure |
|---|---|
| ISSN: | 2364-8228 |
| DOI: | 10.1007/s41109-018-0092-1 |