Evolution of a drug trafficking network: Mapping changes in network structure and function across time

There is a growing body of research using social network analysis to study criminal networks. The great majority of this research examines networks at a single time point. Although there are theoretical approaches which hypothesise on how criminal networks develop and grow, little empirical research has been conducted on the growth of criminal networks over time. This project documents the growth of a drug trafficking network. The aims were to examine and describe structural and functional changes in a criminal network across time. We found that the density of the network remained somewhat stable over time, although the network became more decentralised at the final time point measured. Centrality scores for individual nodes showed significant changes over time. Individuals changed the roles performed across time, consistent with the changing needs and focus of the network. Overall, our results support the characterisation of networks as flexible and adaptive.     

Criminal network vulnerabilities and adaptations

The current paper aimed to investigate the effectiveness of five law enforcement interventions in disrupting and dismantling criminal networks. We tested three law enforcement interventions that targeted social capital in criminal networks (betweenness, degree and cut-set) and two interventions that targeted human capital (actors who possess money and those who possess precursor chemicals). These five interventions are compared with each other and with random (opportunistic) removal of actors in two settings: (i) with network adaptation incorporated into the simulations and (ii) without network adaptation. Results illustrate that the removal of actors based on betweenness centrality was the most efficient strategy, leading to network disruption in the least number of steps and was relatively consistent across replications. Targeting actors who possessed money was the second most effective overall and was also relatively consistent in its disruptive effect.     

Social network analysis as a tool for criminal intelligence: understanding its potential from the perspectives of intelligence analysts

Over the past two decades an increasing number of researchers have applied social network analysis (SNA) to various ‘dark’ networks. This research suggests that SNA is capable of revealing significant insights into the dynamics of dark networks, particularly the identification of critical nodes, which can then be targeted by law enforcement and security agencies for disruption. However, there has so far been very little research into whether and how law enforcement agencies can actually leverage SNA in an operational environment and in particular the challenges agencies face when attempting to apply various network analysis techniques to criminal networks. This paper goes some way towards addressing these issues by drawing on qualitative interviews with criminal intelligence analysts from two Australian state law enforcement agencies. The primary contribution of this paper is to call attention to the organisational characteristics of law enforcement agencies which, we argue, can influence the capacity of criminal intelligence analysts to successfully apply SNA as much as the often citied ‘characteristics of criminal networks’.     

The social network of hackers

Social researchers are facing more and more challenges as criminal networks are expanding in size and moving to the Internet. Many efforts are currently under way to enhance the technical capabilities of researchers working in the field of cybercrimes. Rather than focusing on the technical tools that could enhance research performance, this article focuses on a specific field that has demonstrated its use in the study of criminal networks: social network analysis (SNA). This article evaluates the effectiveness of SNA to enhance the value of information on cybercriminals. This includes both the identification of possible targets for follow-up research as well as the removal of subjects who may be wasting the researchers' time. This article shows that SNA can be useful on two levels. First, SNA provides scientific and objective measures of the structure of networks as well as the position of their key players. Second, fragmentation metrics, which measure the impact of the removal of n nodes in a network, help to determine the amount of resources needed to deal with specific organisations. In this case study, a tactical strike against the network could have had the same destabilising impact as a broader approach. The resources saved by limiting the investigation targets could then be used to monitor the criminal network's reaction to the arrests and to limit its ability to adapt to the post-arrest environment.     

Resilience of a corrupt police network: the first and second jokes in Queensland

Resilient organised crime groups survive and prosper despite law enforcement activity, criminal competition and market forces. Corrupt police networks, like any other crime network, must contain resiliency characteristics if they are to continue operation and avoid being closed down through detection and arrest of their members. This paper examines the resilience of a large corrupt police network, namely The Joke which operated in the Australian state of Queensland for a number of decades. The paper uses social network analysis tools to determine the resilient characteristics of the network. This paper also assumes that these characteristics will be different to those of mainstream organised crime groups because the police network operates within an established policing agency rather than as an independent entity hiding within the broader community.     

Networks within networks: using multiple link types to examine network structure and identify key actors in a drug trafficking operation

Understanding criminal networks can aid in the identification of key players and important relationships within the network. We examined multiple, directed link types in a criminal network. Eight distinct link types were identified, each one related to the exchange of a particular resource (e.g. drugs, money). The analyses focused on the eight link-type network layers and a merged network representing links across all eight layers. We were able to determine the link type of around 31% of the links, and found that nearly 50% of the nodes were involved in more than one network layer. This suggests that many actors contribute in multiple, diverse ways to the operation of the network. Actors were found to specialise in the exchange of particular types of resources, and also to specialise in the strategic position they occupied in the transfer of particular resources.     

网络犯罪刑事管辖权研究

网络空间的全球性、开放性、不确定性和非中心性,使存在于网络空间的网络犯罪对传统的刑事管辖提出了挑战,传统刑事管辖理论似乎难以统领各国网络犯罪管辖实践。对传统刑事管辖理论进行全方位反思,探讨和研究网络犯罪刑事管辖权对理论和实践都具有重要意义。     

Dynamic Attenuation: Terrorism,Transnational Crime and the Role of the US Army Special Forces

This article analyses the ability of the US Army Special Forces to combat illicit networks (criminal and terrorist) through ‘dynamic attenuation’. It is argued that a process of dynamic attenuation, where network ties and not the actors in the network are targeted, should replace the current US strategy of ‘killing or capturing’ criminal agents threatening US interests. By dynamically attenuating (not destroying) the ties between and among criminal actors and criminal organisations, the US can effectively reduce the capability of criminal organisations to operate and achieve their missions (profit and/or terror). This argument is substantiated by assessing the environments where criminal networks thrive, the characteristics of criminal networks, the utility of targeting networks instead of individual actors, and through a comparison of criminal organisations' and US Army Special Forces' strengths and weaknesses. This article concludes with implications and recommendations for US policy in the fight against criminal organisations.     

Co-offending between criminal enterprise groups

Rather than examining networks of individuals as prior research has done, this study systematically examines the structure and composition of co-offending among types of criminal enterprise groups. Using social network analysis, the authors show that different types of crime groups tend to have unique co-offending patterns as measured by network composition and structure. The results also support the countercurrent of criminologists who suggest that ethnically derived categories may be misleading when trying to classify criminal enterprise groups.     

Using social network analysis to target criminal networks

Using social network analysis (SNA), we propose a model for targeting criminal networks. The model we present here is a revised version of our existing model (Schwartz and Rouselle in IALEIA Journal, 18(1):18–14, 2008), which itself builds on Steve Borgatti’s SNA-based key player approach. Whereas Borgatti’s approach focuses solely on actors’ network positions, our model also incorporates the relative strength or potency of actors, as well as the strength of the relationships binding network actors.

犯罪网络分析:社会网络分析在有组织犯罪研究中的应用

在刑事司法领域所使用的"网络"(networks)一词通常是指犯罪组织。一个犯罪网络首先也是一个社会网络,社会网络分析是对社会关系结构及其属性加以分析的一套规范和方法。它主要分析的是不同社会单位(个体、群体或社会)所构成的关系的结构及其属性。自美国"9.11事件"以来,世界各国政府、学者、媒体逐渐认识到社会网络分析在有组织犯罪防控研究中的重要作用,纷纷使用社会网络分析方法对恐怖主义犯罪等有组织犯罪进行犯罪网络分析、研究,通过解构犯罪组织,发现犯罪成员体系、结构特征与行动目标,从而对有组织犯罪进行有效预防和打击。我国应充分认识社会网络分析在现代有组织犯罪防控研究中的重要价值,全面了解国外有关理论与应用发展,积极采取政府资助项目研发与直接设立研究机构等多种手段,促进犯罪网络分析理论与方法在我国的迅速发展。     

From data to disruption

Organized crime groups and law enforcement agencies are caught in complex system similar to a continuous game of cat-and-mouse, in which the latter frequently remains two or more steps behind. Law enforcement agencies are therefore seeking for more proactive strategies in targeting these criminal network structures more effectively. This starts with a better understanding of the way they operate and adapt over time. A key element to developing this understanding remained largely unexploited: big data and big data analytics. This provides novel insight into how criminal cooperations on a micro- and meso level are embedded in small-world criminal macro-networks and how this fosters its resillience against disruption. This paper discusses the opportunities and the limitations of this data-driven approach and its implications for both law enforcement practice and scientific research.     

论网络游戏中虚拟物品的价值属性及其法律保护

互联网的普及与技术的进步,给我们带来了许多发生在网络空间中、甚或现实空间的围绕网络游戏中虚拟物品的纠纷。有关网络游戏中虚拟财产的法律性质不明确,通过司法途径解决类似的网络游戏纠纷存在诸多不确定的因素,对虚拟财产的保护处于无奈的状态。从经济学及法学的角度分析,很有对网络游戏中虚拟物品及其权益进行保护的必要性。对网络游戏中虚拟物品及其权益进行保护,可以从民法、刑法、网络法的制定与完善上进行。     

Leadership protection in drug-trafficking networks

Effective leadership is a crucial component in organisational success. This also applies to criminal networks that have the added challenge of operating in a high-risk hostile environment. While criminal networks commonly employ communicative and structural practices meant to buffer leadership from exogenous threats, there has been little empirical examination as to their effectiveness. In this article, we review the research literature on the various approaches that profit-oriented illicit networks employ to protect their leaders. We then present sociometric and qualitative data from a previously unexamined drug-trafficking network (the Prada cocaine-trafficking network) as a case study on leadership protection tactics employed by illicit entrepreneurial networks. Results of our analysis are discussed in the conclusion, along with study limitations and areas for future research.     

Friends with(out) benefits: co-offending and re-arrest

Research shows that co-offending has contradictory effects on rates of re-arrest. On the one hand, group offending may be riskier: for example, co-offenders might be targeted by police or might snitch to protect themselves. Criminal networks may also have indirect effects: offenders embedded in criminal networks commit more offences and thus should have a higher risk of being arrested at some point. On the other hand, networks generate steady criminal opportunities with relatively low risk of arrest and high monetary benefits (e.g. drug trafficking). Few authors have empirically explored the relation between co-offending and re-arrest. This article does so using data from seven years of arrest records in the province of Quebec, Canada. The analysis is designed to explore why some offenders are re-arrested after an initial arrest while others are not. It focuses on the factors involved in re-arrest, considering two distinct levels of measures of co-offending. The first level of analysis takes into account a situational measure that indicates whether a given offence was committed by co-offenders (group offence). The second level is used to examine whether being part of a criminal network influences re-arrest. For offenders embedded in such networks, two network features (degree centrality and clustering coefficient) show that the global position of individuals within the Quebec arrest network are analysed. Our results suggest that co-offending is a crucial factor that should be taken into account when looking at the odds of being caught again. The use of generalised linear mixed model brings interesting nuances about the impact of co-offending. The article adds to the recently growing literature on the link between networks and criminal careers.