Daniel A. Eisenberg

Resilience metrics for cyber systems

As federal agencies and businesses rely more on cyber infrastructure, they are increasingly vulnerable to cyber attacks that can cause damages disproportionate to the sophistication and cost to launch the attack. In response, regulatory authorities call for focusing attention on enhancing infrastructure resilience. For example, in the USA, President Obama issued an Executive Order and policy directives focusing on improving the resilience and security of cyber infrastructure to a wide range of cyber threats. Despite the national and international importance, resilience metrics to inform management decisions are still in the early stages of development. We apply the resilience matrix framework developed by Linkov et al. (Environ Sci Technol 47:10108–10110, 2013) to develop and organize effective resilience metrics for cyber systems. These metrics link national policy goals to specific system measures, such that resource allocation decisions can be translated into actionable interventions and investments. In this paper, a number of metrics have been identified and assessed using quantitative and qualitative measures found in the literature. We have proposed a generic approach and could integrate actual data, technical judgment, and literature-based measures to assess system resilience across physical, information, cognitive, and social domains.

Illustrating Anticipatory Life Cycle Assessment for Emerging Photovoltaic Technologies

Current research policy and strategy documents recommend applying life cycle assessment (LCA) early in research and development (R&D) to guide emerging technologies toward decreased environmental burden. However, existing LCA practices are ill-suited to support these recommendations. Barriers related to data availability, rapid technology change, and isolation of environmental from technical research inhibit application of LCA to developing technologies. Overcoming these challenges requires methodological advances that help identify environmental opportunities prior to large R&D investments. Such an anticipatory approach to LCA requires synthesis of social, environmental, and technical knowledge beyond the capabilities of current practices. This paper introduces a novel framework for anticipatory LCA that incorporates technology forecasting, risk research, social engagement, and comparative impact assessment, then applies this framework to photovoltaic (PV) technologies. These examples illustrate the potential for anticipatory LCA to prioritize research questions and help guide environmentally responsible innovation of emerging technologies.

Anticipatory life-cycle assessment for responsible research and innovation

The goal of guiding innovation toward beneficial social and environmental outcomes – referred to in the growing literature as responsible research and innovation (RRI) – is intuitively worthwhile but lacks practicable tools for implementation. One potentially useful tool is life-cycle assessment (LCA), which is a comprehensive framework used to evaluate the environmental impacts of products, processes, and technologies. However, LCA ineffectively promotes RRI for at least two reasons: (1) Codified approaches to LCA are largely retrospective, relying heavily on data collected from mature industries with existing supply chains and (2) LCA underemphasizes the importance of stakeholder engagement to inform critical modeling decisions which diminishes the social credibility and relevance of results. LCA researchers have made piecemeal advances that address these shortcomings, yet there is no consensus regarding how to advance LCA to support RRI of emerging technologies. This paper advocates for development of ...

Benchmarking agency and organizational practices in resilience decision making

Recent directives from the US Office of the President have detailed the need for resilience in the face of increased security threats and natural disasters. While these documents call for resilience improvements, no guiding framework for the assessment of resilience exists. Federal agencies are then deriving individual ways to address resilience, resulting in a series of parallel efforts instead of one national cohesive effort. This paper summarizes the portfolio of current efforts implemented by agencies to guide the integration of resilience assessment across the federal government. We present a critical overview on the state of resilience science within seven federal agencies and our perspective on the consistencies and disparities on how each agency is enacting presidential orders. The resulting analysis identifies differences in approaches to resilience and common ground upon which federal agencies can use to support more effective programs.

Extreme events in multilayer, interdependent complex networks and control

We investigate the emergence of extreme events in interdependent networks. We introduce an inter-layer traffic resource competing mechanism to account for the limited capacity associated with distinct network layers. A striking finding is that, when the number of network layers and/or the overlap among the layers are increased, extreme events can emerge in a cascading manner on a global scale. Asymptotically, there are two stable absorption states: a state free of extreme events and a state of full of extreme events, and the transition between them is abrupt. Our results indicate that internal interactions in the multiplex system can yield qualitatively distinct phenomena associated with extreme events that do not occur for independent network layers. An implication is that, e.g., public resource competitions among different service providers can lead to a higher resource requirement than naively expected. We derive an analytical theory to understand the emergence of global-scale extreme events based on the concept of effective betweenness. We also articulate a cost-effective control scheme through increasing the capacity of very few hubs to suppress the cascading process of extreme events so as to protect the entire multi-layer infrastructure against global-scale breakdown.

Redesigning Resilient Infrastructure Research

Despite federal policy directives to strengthen the resilience of critical infrastructure systems to extreme weather and other adverse events, several knowledge and governance barriers currently frustrate progress towards policy goals, namely: (1) a lack of awareness of what constitutes resilience in diverse infrastructure applications, (2) a lack of judgement about how to create resilience, (3) a lack of incentives that motivate resilience creation, and (4) obstacles that prevent action or reform, even where incentives exist, within existing governance systems. In this chapter, we describe each of these barriers in greater detail and provide a catalog of theories for overcoming them. Regarding awareness, we contrast four different characterizations of resilience as rebound, robustness, graceful extensibility, and sustained adaptability. We apply Integral Theory to demonstrate the necessity of integrating multiple investigative perspectives. Further, we illustrate the importance of recognizing resilience as a set of processes, in addition to resources and outcomes, and the difficulty of measuring quality and quality of resilience actions. Regarding judgement, we position infrastructure as the principal mechanism by which human rights are realized as human capabilities, and propose applying theories of human development such as Maslow’s hierarchy of needs to identify the most critical infrastructure in terms of the services they provide to end users. Regarding a lack of incentives, we examine the modes and tools of financial analysis by which investments in resilience infrastructure may be prioritized and find two failings: the difficulty of estimating the monetary value of optionality, and the problem of exponential discounting of future cash flows. Regarding obstacles to action, we describe a hierarchy of adaptive actions applicable to physical infrastructure and the essential dimensions of organizational maturity that determine how these adaptive actions might be initiated. Additionally, we discuss the difficulty of education and training for resilient infrastructure systems and propose simulation gaming as an integrative research and education approach for capturing lessons learned from historical catastrophes, play-testing scenarios, sharing knowledge, and training a workforce prepared for the challenges of the post-industrial infrastructure age. Finally, we suggest establishing a National Network for Resilient Infrastructure Simulation to coordinate research and practice focused on interactive case studies in resilient infrastructure systems.

Optimization and resilience of complex supply-demand networks

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers. We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

Fail-safe and safe-to-fail adaptation: decision-making for urban flooding under climate change

As climate change affects precipitation patterns, urban infrastructure may become more vulnerable to flooding. Flooding mitigation strategies must be developed such that the failure of infrastructure does not compromise people, activities, or other infrastructure. “Safe-to-fail” is an emerging paradigm that broadly describes adaptation scenarios that allow infrastructure to fail but control or minimize the consequences of the failure. Traditionally, infrastructure is designed as “fail-safe” where they provide robust protection when the risks are accurately predicted within a designed safety factor. However, the risks and uncertainties faced by urban infrastructure are becoming so great due to climate change that the “fail-safe” paradigm should be questioned. We propose a framework to assess potential flooding solutions based on multiple infrastructure resilience characteristics using a multi-criteria decision analysis (MCDA) analytic hierarchy process algorithm to prioritize “safe-to-fail” and “fail-safe” strategies depending on stakeholder preferences. Using urban flooding in Phoenix, Arizona, as a case study, we first estimate flooding intensity and evaluate roadway vulnerability using the Storm Water Management Model for a series of downpours that occurred on September 8, 2014. Results show the roadway types and locations that are vulnerable. Next, we identify a suite of adaptation strategies and characteristics of these strategies and attempt to more explicitly categorize flooding solutions as “safe-to-fail” and “fail-safe” with these characteristics. Lastly, we use MCDA to show how adaptation strategy rankings change when stakeholders have different preferences for particular adaptation characteristics.

The vulnerability of interdependent urban infrastructure systems to climate change: could Phoenix experience a Katrina of extreme heat?

Abstract Continued growth in the American Southwest depends on the reliable delivery of services by critical infrastructure systems, including water, power, and transportation. As these systems age, they are increasingly vulnerable to extreme heat events that both increase infrastructure demands and reveal complex interdependencies that amplify stressors. While the traditional analytic approach to preparing for such hazards is risk analysis, the experience of Hurricane Katrina provides a warning of the limitations of risk-based approaches for confronting complexity, and the potential scale and impact that can result from cascading failures under extreme stress. By contrast, this research is the first to apply resilience theory to understanding complex infrastructure interdependencies during an extreme heat event in Phoenix, AZ and the role of sensing, anticipating, adapting, and learning (SAAL) for mitigating catastrophe.

The "weak" interdependence of infrastructure systems produces mixed percolation transitions in multilayer networks

Previous studies of multilayer network robustness model cascading failures via a node-to-node percolation process that assumes “strong” interdependence across layers–once a node in any layer fails, its neighbors in other layers fail immediately and completely with all links removed. This assumption is not true of real interdependent infrastructures that have emergency procedures to buffer against cascades. In this work, we consider a node-to-link failure propagation mechanism and establish “weak” interdependence across layers via a tolerance parameter α which quantifies the likelihood that a node survives when one of its interdependent neighbors fails. Analytical and numerical results show that weak interdependence produces a striking phenomenon: layers at different positions within the multilayer system experience distinct percolation transitions. Especially, layers with high super degree values percolate in an abrupt manner, while those with low super degree values exhibit both continuous and discontinuous transitions. This novel phenomenon we call mixed percolation transitions has significant implications for network robustness. Previous results that do not consider cascade tolerance and layer super degree may be under- or over-estimating the vulnerability of real systems. Moreover, our model reveals how nodal protection activities influence failure dynamics in interdependent, multilayer systems.