Disrupting terrorist and other covert networks requires identifying and capturing key leaders. Previous research by Martonosi et al. (2009) defines a load metric on vertices of a covert network representing the amount of communication in which a vertex is expected to participate. They suggest that the visibility of a target vertex can be increased by removing other, more accessible members of the network. This report evaluates the feasibility of efficiently calculating the optimal subset of vertices to remove. We begin by proving that the general problem of identifying the optimally load maximizing vertex set removal is NP-complete. We then consider the feasibility of more quickly computing the load maximizing single vertex removal by designing an efficient algorithm for recomputing Gomory- Hu trees. This leads to a result regarding the uniqueness of Gomory- Hu trees with implications towards the feasibility of one approach for Gomory- Hu tree reconstruction. Finally, we propose a warm start algorithm which performs this reconstruction, and analyze its runtime experimentally.

This thesis seeks to extend the application of Social Network Analysis (SNA) to temporal graphs, in particular providing new insights for the understanding of covert networks. The analyses undertaken reveal informative features and properties of individuals' affiliations under covertness that also illustrate how both individuals and events influence the network structure. The review of the literature on covert networks provided in the initial two chapters suggests the presence of some ambiguities concerning how authors define structural properties and dynamics of covert networks. Authors sometimes disagree and use their findings to explain opposite views about covert networks. The controversy in the field is used as a starting point in order to justify the methodological application of SNA to understand how individuals involved in criminal and illegal activities interact with each other. I attempt to use a deductive approach, without preconceived notions about covert network characteristics. In particular, I avoid considering covert networks as organisations in themselves or as cohesive groups. I focus on individuals and their linkages constructed from their common participation in illicit events such as secret meetings, bombing attacks and criminal operations. In order to tackle these processes I developed innovative methods for investigating criminals' behaviours over time and their willingness to exchange tacit information. The strategy implies the formulation of a network model in order to represent and incorporate in a graph three types of information: individuals, events, and the temporal dimension of events. The inclusion of the temporal dimension offers the possibility of adopting a more comprehensive theoretical framework for considering individuals and event affiliations. This thesis expands the analysis of bipartite covert networks by adopting several avenues to explore in this perspective. Chapter 3 proposes a different way to represent two-mode networks starting from the use of line-graphs, namely the bi-dynamic line-graph data representation (BDLG), through which it is possible to represent the temporal evolution of individual's trajectories. The following chapter 4 presents some reflections about the idea of cohesion and cohesive subgroups specific to the case of two-mode networks. Based on the affiliation matrices, the analysis of local clustering through bi-cliques offers an attempt to analyse the mechanism of selecting accomplices while taking into account time. Chapter 5 is concerned with the concept of centrality of individuals involved in flows of knowledge exchanges. The theoretical and analytical framework helps in elaborating how individuals share their acquired hands-on experiences with others by attending joint task activities over time. Chapter 6 provides an application of the approaches introduced in the preceding chapters to the specific case of the Noordin Top terrorist network. Here, the knowledge of experience flow centrality measure opens up a new way to quantify the transmission of information and investigate the formation of the criminal capital. Finally, the last Chapter 7 presents some future research extensions by illustrating the versatility of the proposed approaches in order to provide new insights for the understanding of criminals' behaviours.

Social network analysis is a fruitful approach to the study of relations and interaction between actors involved in organized crime. This dissertation utilizes network perspective to study several cases of organized criminal groups. It is divided into eight chapters. The first introductory chapter is followed by a chapter reviewing the most important network concepts, measures, and models, and their application in the study of organized crime. The four subsequent chapters are empirical studies. The third chapter is a case study of a political corruption network, known as the Rath affair. The study shows that the network consists of different, sometimes overlapping, relations (multiplexity), namely collaboration, resource transfer, and pre-existing ties. The network shows a clear core-periphery structure with politicians forming a dense core and businesspeople occupying periphery. The following chapter studies a case of counterfeit alcohol distribution network, known as the methanol affair. The network structure is composed of two subgroups bridged by one tie, permitting relatively efficient distribution of the beverages. Furthermore, statistical models point out the importance of triadic closure and pre-existing ties for the formation of ties in the network. The fifth chapter tests an influential theory in...