Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

Centrality in the Global Network of Corporate Control

Abstract: Corporations across the world are highly interconnected in a large global network of corporate control. This paper investigates the global board interlock network, covering 400,000 firms linked through 1,700,000 edges representing shared directors between these firms. The main focus is on the concept of centrality, which is used to investigate the embeddedness of firms from a particular country within the global network. The study results in three contributions. First, to the best of our knowledge for the first time we can investigate the topology as well as the concept of centrality in corporate networks at a global scale, allowing for the largest cross-country comparison ever done in interlocking directorates literature. We demonstrate, amongst other things, extremely similar network topologies, yet large differences between countries when it comes to the relation between economic prominence indicators and firm centrality. Second, we introduce two new metrics that are specifically suitable for comparing the centrality ranking of a partition to that of the full network. Using the notion of centrality persistence we propose to measure the persistence of a partition's centrality ranking in the full network. In the board interlock network, it allows us to assess the extent to which the footprint of a national network is still present within the global network. Next, the measure of centrality ranking dominance tells us whether a partition (country) is more dominant at the top or the bottom of the centrality ranking of the full (global) network. Finally, comparing these two new measures of persistence and dominance between different countries allows us to classify these countries based the their embeddedness, measured using the relation between the centrality of a country's firms on the national and the global scale of the board interlock network.

Scalable security analysis in hierarchical attack representation model using centrality measures

Abstract: Network security can be analysed using attack representation models (ARMs) (e.g., Attack Graphs (AGs) and Attack Trees (ATs)). One can analyse the network security by computing all possible attack scenarios, but it suffers from a scalability problem. We propose centrality based network security analysis by ranking important hosts based on network centrality measures, and vulnerabilities based on security metric values. We used two-layer hierarchical attack representation model to evaluate the network security, by taking into account importance of hosts and vulnerabilities in the upper and the lower layers, respectively. We define a new centrality measure based on the location of an attacker and a target. We simulate security analysis using centrality measures comparing with an exhaustive search method. Further, we investigate the performance when the location of the attacker is different in the network.

Signal flow graphs-Computer-aided system analysis and sensitivity calculations

Abstract: Concepts which promise to extend many fundamental results of network theory to general systems are introduced. The basis for these extensions is the introduction of two matrices, the summing matrix S and the branching matrix B, which completely describe the topology of a signal flow graph. This leads to a formulation of system equations in terms of submatrices of the S- and B-matrices suitable for digital-computer programming. Consequently, many computer-aided circuit analysis and design programs can now be employed for the computer-aided analysis and design of systems representable by signal flow graphs. This formulation also leads to a straightforward algorithm for obtaining the system gain, an alternate to using Mason's gain formula. Furthermore, the power of this formulation, and its strong relation to network theory, is demonstrated by the derivation of a theorem similar to Tellegen's theorem in network theory. The theorem depends only on the topological properties of the summing and branching matrices and not on the functional relationships between the branch

Temporal qualitative analysis: explaining how physical systems work

Abstract: A theory of design that proposes fundamental changes to a system's behavior must capture a designer's understanding of how physical systems work. To be versatile, such a theory must provide a link between the intuitions of a designer and the corresponding principles of formal theory (i.e., algebra, calculus, feedback analysis, network theory, and electrodynamics) which makes each underlying assumption explicit. Temporal qualitative analysis is a domain independent technique for analyzing the qualitative large signal behavior of continuous physical systems that captures a designer's intuitions of causality, change, continuity, energy storage and feedback. Temporal qualitative analysis is based on four major components that are demonstrated in the domain of circuit analysis. First, a qualitative representation is composed of a set of open regions separated by boundaries. These boundaries are chosen at the appropriate level of detail for the analysis. This concept is used in modeling time, space, system state variables, and device operating regions. Second, constraints between state variables are established by circuit theory. At a finer time scale, the designer's intuition of electrodynamics is used to impose a causal relationship among these constraints. Third, large signal behavior is modeled by transition analysis, using continuity and theorems of calculus to determine how quantities pass between regions over time. Finally, feedback analysis uses knowledge about the structure of equations and the properties of structure classes to resolve ambiguities.

Temporal Changes in Local Topology of an Email-Based Social Network

Abstract: The dynamics of complex social networks has become one of the research areas of growing importance. The knowledge about temporal changes of the network topology and characteristics is crucial in networked communication systems in which accurate predictions are important. The local network topology can be described by the means of network motifs which are small subgraphs -- usually containing from 3 to 7 nodes. They were shown to be useful for creating profiles that reveal several properties of the network. In this paper, the time-varying characteristics of social networks, such as the number of nodes and edges as well as clustering coefficients and different centrality measures are investigated. At the same time, the analysis of three-node motifs (triads) was used to track the temporal changes in the structure of a large social network derived from e-mail communication between university employees. We have shown that temporal changes in local connection patterns of the social network are indeed correlated with the changes in the clustering coefficient as well as various centrality measures values and are detectable by means of motifs analysis. Together with robust sampling network motifs can provide an appealing way to monitor and assess temporal changes in large social networks.