Growth and containment of a hierarchical criminal network

Abstract

We model the hierarchical evolution of an organized criminal network via antagonistic recruitment and pursuit processes. Within the recruitment phase, a criminal kingpin enlists new members into the network, who in turn seek out other affiliates. New recruits are linked to established criminals according to a probability distribution that depends on the current network structure. At the same time, law enforcement agents attempt to dismantle the growing organization using pursuit strategies that initiate on the lower level nodes and that unfold as self-avoiding random walks. The global details of the organization are unknown to law enforcement, who must explore the hierarchy node by node. We halt the pursuit when certain local criteria of the network are uncovered, encoding if and when an arrest is made; the criminal network is assumed to be eradicated if the kingpin is arrested. We first analyze recruitment and study the large scale properties of the growing network; later we add pursuit and use numerical simulations to study the eradication probability in the case of three pursuit strategies, the time to first eradication and related costs. Within the context of this model, we find that eradication becomes increasingly costly as the network increases in size and that the optimal way of arresting the kingpin is to intervene at the early stages of network formation. We discuss our results in the context of dark network disruption and their implications on possible law enforcement strategies.

Combined Heuristic Attack Strategy on Complex Networks

“…Under such term, terrorist networks, fake-news spreading networks, malnets or botnets used in DDoS attacks, or for spreading worms and viruses, dark networks involved in various criminal activities like illegal arm selling or child pornography, and so forth can be understood [14][15][16][17][18][19][20]. Attack strategies on such harmful complex networks (i.e., node deletion and occasionally also edge deletion) are studied in [21][22][23].…”

Corruption and complexity: a scientific framework for the analysis of corruption networks

“…The importance of the application of multidisciplinary and scientific approaches such as complex systems, network theory, and even physics, to the study of criminal activities was presented by the end of last century (Sparrow, 1991). However, it was until the last decades that these types of studies have begun to gain momentum given the great progress in computing and data science (Caldarelli et al, 2018) and their enormous relevance in modern social, economic, and political contexts (D'Orsogna & Perc, 2015;Helbing et al, 2015;Espinal-Enríquez & Larralde, 2015;Marshak, Rombach, Bertozzi & D'Orsogna, 2016;DellaPosta, 2017;Fazekas, Skuhrovec & Wachs, 2017;Morselli & Boivin, 2017;Altshuler & Pentland, 2018;Magliocca et al, 2019;Ouellet, Bouchard & Charette, 2019;Niu, Elsisy, Derzsy, & Szymanski, 2019).…”

Intelligent deception techniques against adversarial attack on the industrial system

“…The leader's information is very important to get confidential information and the planned future terrorist activities in the network. Marshak et al 15 developed a hierarchical evolution of a terrorist network via the recruitment of people according to their affiliations. At the same time, security agents try to break the organization through pursuit strategy.…”

“…The community detection algorithms (CDAs) have been designed to unveil some essential insights, such as human interactions in social networks, 9,10 subject descriptions in information networks, 11,12 interaction between neurons, 13 the association among terrorists in the criminal network, 14,15 and so forth. Community identification tools raise multiple considerable privacy concerns.…”