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

Finding weighted positive influence dominating set to make impact to negatives: a study on online social networks in the new millennium

In the new millennium, information and communication technologies (ICTs) such as the internet and mobile phones have been developed rapidly. These new technologies have changed people's communication patterns and provided new ways of maintaining online social networks which play ever-important roles in shaping the behavior of users on the web in the new millennium. ICTs also offer new computational models and data to investigate the dynamics and structure of exploiting the relationships and influences among individuals in online social networks. As an example, users on Wikipedia can vote for or against the nomination of others to adminship; users on Epinions can express trust or distrust of others. These facts illustrate that the relationship among the users of online social networks can be either positive or negative. The chapter will investigate negative as well as positive relationships of users in online social networks. We will focus on a novel dominating set named Weighted Positive Influence Dominating Set (WPIDS) problem arising from some social problems

The importance of centralities in dark network value chains

This paper introduces three novel centrality measures based on the nodes’ role in the operation of a joint task, i.e., their position in a criminal network value chain. For this, we consider networks where nodes have attributes describing their "capabilities" or "colors", i.e., the possible roles they may play in a value chain. A value chain here is understood as a series of tasks to be performed in a specific order, each requiring a specific capability. The first centrality notion measures how many value chain instances a given node participates in. The other two assess the costs of replacing a node in the value chain in case the given node is no longer available to perform the task. The first of them considers the direct distance (shortest path length) between the node in question and its nearest replacement, while the second evaluates the actual replacement process, assuming that preceding and following nodes in the network should each be able to find and contact the replacement. In this report, we demonstrate the properties of the new centrality measures using a few toy examples and compare them to classic centralities, such as betweenness, closeness and degree centrality. We also apply the new measures to randomly colored empirical networks. We find that the newly introduced centralities differ sufficiently from the classic measures, pointing towards different aspects of the network. Our results also pinpoint the difference between having a replacement node in the network and being able to find one. This is the reason why "introduction distance" often has a noticeable correlation with betweenness. Our studies show that projecting value chains over networks may significantly alter the nodes’ perceived importance. These insights might have important implications for the way law enforcement or intelligence agencies look at the effectiveness of dark network disruption strategies over time