Contrasting Views of Complexity and Their Implications For Network-Centric Infrastructures

There exists a widely recognized need to better understand and manage complex “systems of systems,” ranging from biology, ecology, and medicine to network-centric technologies. This is motivating the search for universal laws of highly evolved systems and driving demand for new mathematics and methods that are consistent, integrative, and predictive. However, the theoretical frameworks available today are not merely fragmented but sometimes contradictory and incompatible. We argue that complexity arises in highly evolved biological and technological systems primarily to provide mechanisms to create robustness. However, this complexity itself can be a source of new fragility, leading to “robust yet fragile” tradeoffs in system design. We focus on the role of robustness and architecture in networked infrastructures, and we highlight recent advances in the theory of distributed control driven by network technologies. This view of complexity in highly organized technological and biological systems is fundamentally different from the dominant perspective in the mainstream sciences, which downplays function, constraints, and tradeoffs, and tends to minimize the role of organization and design

Mathematical problems for complex networks

Copyright @ 2012 Zidong Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is made available through the Brunel Open Access Publishing Fund.Complex networks do exist in our lives. The brain is a neural network. The global economy is a network of national economies. Computer viruses routinely spread through the Internet. Food-webs, ecosystems, and metabolic pathways can be represented by networks. Energy is distributed through transportation networks in living organisms, man-made infrastructures, and other physical systems. Dynamic behaviors of complex networks, such as stability, periodic oscillation, bifurcation, or even chaos, are ubiquitous in the real world and often reconfigurable. Networks have been studied in the context of dynamical systems in a range of disciplines. However, until recently there has been relatively little work that treats dynamics as a function of network structure, where the states of both the nodes and the edges can change, and the topology of the network itself often evolves in time. Some major problems have not been fully investigated, such as the behavior of stability, synchronization and chaos control for complex networks, as well as their applications in, for example, communication and bioinformatics

Codifying Information Assurance Controls for Department of Defense (DoD) Supervisory Control and Data Acquisition (SCADA) Systems (U)

Protecting DoD critical infrastructure resources and Supervisory Control and Data Acquisition (SCADA) systems from cyber attacks is becoming an increasingly challenging task. DoD Information Assurance controls provide a sound framework to achieve an appropriate level of confidentiality, integrity, and availability. However, these controls have not been updated since 2003 and currently do not adequately address the security of DoD SCADA systems. This research sampled U.S. Air Force Civil Engineering subject matter experts representing eight Major Commands that manage and operate SCADA systems. They ranked 30 IA controls in three categories, and evaluated eight SCADA specific IA controls for inclusion into the DoD IA control framework. Spearman’s Rho ranking results (ρ = .972414) indicate a high preference for encryption, and system and information integrity as key IA Controls to mitigate cyber risk. Equally interesting was the strong agreement among raters on ranking certification and accreditation dead last as an effective IA control. The respondents strongly favored including four new IA controls of the eight considered