System and Sector Interdependencies: An Overview
15 Mar 2009-pp 1-20
TL;DR: In this paper, the authors define infrastructure interdependencies and introduce basic terminology, analytical approaches, research and development needs, and the range of interdisciplinary skills required for a comprehensive analysis of infrastructure.
Abstract: This introductory article provides a foundation for the remaining articles of this handbook by defining infrastructure interdependencies and introducing basic terminology, analytical approaches, research and development needs, and the range of interdisciplinary skills required for a comprehensive analysis of infrastructure and interdependencies. Traditional analysis of interdependencies involves the characterization of infrastructure-to-infrastructure linkages to identify the key infrastructure components that, if lost or degraded, could adversely affect the performance of other infrastructures. Such analysis is motivated by the recognition that a series of incidents could interact (cascade) across critical infrastructures to degrade the services upon which all depend. From a more comprehensive risk assessment and management perspective, interdependencies analysis must also involve the identification and characterization of a wide range of threats (natural and accidental, systems related, and intentional), vulnerabilities (physical, cyber, and human), and consequences of loss (e.g. health and safety, economic, national security, environmental, and sociopolitical). Such an all-hazards approach provides a framework for making defensible, cost-effective infrastructure protection and operation decisions to ensure the security and resilience of the interdependent systems that underpin our society.
Keywords:
infrastructure interdependencies;
cascading failure;
risk management;
resilience
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TL;DR: To better understand CISs to support planning, maintenance and emergency decision making, modeling and simulation of interdependencies across CISs has recently become a key field of study and this paper reviews the studies in the field and broadly groups the existing modeling and Simulation approaches into six types.
891 citations
TL;DR: In this article, the authors focus on the mutual interdependencies among key stakeholders in such situations and emphasize the need for changes in thinking, particularly concerning the ability to define problems across conventional administrative structures, geographical boundaries and conferred powers.
Abstract: The functioning and resilience of modern societies have become more and more dependent on critical infrastructures. Severe disturbance to critical infrastructure is likely to reveal chaotic operational conditions, in which infrastructure service providers, emergency services, police, municipalities, and other key stakeholders must act effectively to minimize damages and restore normal operations. This paper aims to better understand this kind of operational environment resulting from, for example, a terrorist attack. It emphasizes mutual interdependencies among key stakeholders in such situations. The empirical contribution is based on observations from a workshop, in which participants representing the critical services and infrastructures in Finland discussed in thematic groups. Two scenarios guided the workshop discussions; nationwide electricity grid disruption and presumably intentionally contaminated water supply in a city. The results indicate that more attention should be paid to the interdependencies between critical infrastructures, as well as to the latent vulnerabilities hidden inside the systems. Furthermore, producing security seems to require continuous interaction and creation of meanings between extremely different actors and logics. This implies a need for changes in thinking, particularly concerning the ability to define problems across conventional administrative structures, geographical boundaries and conferred powers.
21 citations
TL;DR: In this paper, the authors suggest a more encompassing approach to learning, and essentially, a new mindset for training preparedness that would better equip emergency response actors when they come face-to-face with the unthinkable.
Abstract: The increasing complexity of critical infrastructure subjects it to problems that are even more wicked, unexpected, and unthinkable than the ones faced before. Hence, the lessons that are drawn from the previous experiences and absorbed into preparedness schemes and planning may well become part of the problem rather than core elements in their effective resolution. This article scrutinizes the potential for the emergence of such a mismatch in the case of a severe disruption to critical infrastructure. As a remedy, we suggest a more encompassing approach to learning, and essentially, a new mindset for training preparedness that would better equip emergency response actors when they come face-to-face with the unthinkable. Based on research, it is advisable to be cautious of relying too much on what is known with certainty. In addition, this study raises doubts as to whether training inevitably improves the ability to act in exceptional situations.
6 citations
TL;DR: This study presents a novel framework for building a resilience and vulnerability-informed decision support system (RV-DSS) that quantifies benefits of considering interdependencies in streamlining strategies for interdependent systems and proposes a measure of network resilience in response to hazardous events.
6 citations
28 Sep 2020
TL;DR: This study developed a graph-theory based analysis framework to model the interdependencies between the electric power and transportation infrastructure systems– road networks and reports the results from a case study in Seattle, Washington considering different scenarios.
Abstract: The critical infrastructure (CI) elements in the United States are highly interconnected and interdependent. Recent cases of extreme events–either nature or human-caused– have demonstrated ripple effects propagating from one critical infrastructure to another reflecting the interdependencies. Among many CIs, the electric power and transportation infrastructure systems exhibit a higher level of interdependencies, and it is vital to model electric power and transportation infrastructure system holistically to understand the vulnerable states from temporal and spatial dimensions considering interconnectedness and cascading effects. This study developed a graph-theory based analysis framework to model the interdependencies between the electric power and transportation infrastructure systems– road networks. The CI elements are integrated by building a heterogeneous graph that includes transportation road sections, electrical substations, utility headquarters, traffic signal nodes, and other relevant CI nodes. We report the results from a case study in Seattle, Washington considering different scenarios– network disruption types, traffic congestion level, and uncertainty in restoration time.
2 citations
Cites background from "System and Sector Interdependencies..."
...CIS are often modeled as a network of complex adaptive systems to accommodate topological diversity, emergence of network features, and complex interdependencies [6], [9], [10]....
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References
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TL;DR: The Inoperability Input-Output Model (IIM) as mentioned in this paper is based on Leontief's input-output model, which characterizes interdependencies among sectors in the economy and analyzes initial disruptions to a set of sectors and the resulting ripple effects.
Abstract: The paper discusses the theory and methodology supporting the development of the inoperability input-output model (IIM). The IIM is based on Leontief’s input-output model, which characterizes interdependencies among sectors in the economy and analyzes initial disruptions to a set of sectors and the resulting ripple effects. An advantage of building on Leontief’s model is that it is supported by publications of the Bureau of Economic Analysis. Independent computer runs of the IIM can represent the entire nation or sectors within particular U.S. regions. A dynamic extension of the IIM analyzes different temporal frames of recovery and characterizes the required sector adjustments for achieving new production levels. The IIM can systemically prioritize and manage the sectors deemed to be economically critical and also identify those sectors whose continued operability is critical during recovery. A companion paper demonstrates applying the IIM to attacks on electric power and telecommunications.
360 citations
TL;DR: The infrastructure interdependency assessment process, modelling tools developed to support that process and examples of assessment results are presented.
Abstract: Infrastructures are a complex set of interconnected, interdependent, adaptive systems on which the nation, manufacturing systems and individuals depend. Understanding the potential consequences of infrastructure interdependencies, as the infrastructures evolve and the regulations governing their operation change, is at the heart of our infrastructure interdependencies research program. This program includes development of analysis methods and simulation tools for evaluating the potential effects of disruptions and for prioritising risks. Fundamental infrastructures simulated using these tools include; transportation, telecommunications, electric power, banking and finance, water, agriculture, emergency services, fossil fuels, and government. The complexity of the infrastructures and their interactions prevent us from knowing a priori how these interactions will influence individuals, states or the nation; the consequences of policy decisions; vulnerabilities due to interdependencies, natural disasters, malevolent threats and aging; or vulnerabilities that need to be eliminated in order to assure individual, state or national economic security. The goal of the interdependency analyses is to identify significant risks to critical systems, arising from interconnection, and effective mechanisms for mitigating those risks. This article presents the infrastructure interdependency assessment process, modelling tools developed to support that process and examples of assessment results.
137 citations