A Two-Stage Approach to Simulate Interdependent Critical Infrastructures

Critical infrastructures (CI) are designated sectors that if incapacitated or destroyed by natural disasters would have a serious impact on national security and economic and social welfare. Due to the interdependency of critical infrastructures failure of one infrastructure during a natural disaster such as earthquake or flood may cause failure of another and so on through a cascade or escalating effect. Quantification of these types of interdependencies between critical infrastructures is essential for effective response and management of resources for rescue, recovery, and restoration during times of crises. This paper proposes a new mathematical framework based on an asymmetric relation matrix constructed in a bottom-up approach for modeling and analyzing interdependencies of critical infrastructures. Asymmetric dependency matrices can be constructed using the asymmetric incidence coefficient based on node-level relationships defined between nodes for measuring the strength of interdependency between node and node, node and network, and networks and networks. These asymmetric matrices are further analyzed for ranking infrastructures in terms of their relative importance and for identifying nodes and infrastructure networks that play a critical role in chain effects among infrastructures involved in geo-disaster events such as flooding. Examples of interdependency analysis for the identification of vulnerabilities among fifteen national defense-related infrastructure sectors by the Australian government and a simulated example using the newly developed GIS-based network simulator GeoPN are used to validate and demonstrate the implementation and effectiveness of interdependency analysis methods in analyzing infrastructure interdependency during a flooding event.

Modeling the resilience of interdependent critical infrastructure (ICI) requires a careful assessment of interdependencies as these systems are becoming increasingly interconnected. The interdependent connections across ICIs are often subject to uncertainty due to the lack of relevant data. Yet, this uncertainty has not been properly characterized. This paper develops an approach to model the resilience of ICIs founded in probabilistic graphical models. The uncertainty of interdependency links between ICIs is modeled using stochastic block models (SBMs). Specifically, the approach estimates the probability of links between individual systems considered as blocks in the SBM. The proposed model employs several attributes as predictors. Two recovery strategies based on static and dynamic component importance ranking are developed and compared. The proposed approach is illustrated with a case study of the interdependent water and power networks in Shelby County, TN. Results show that the probability of interdependency links varies depending on the predictors considered in the estimation. Accounting for the uncertainty in interdependency links allows for a dynamic recovery process. A recovery strategy based on dynamically updated component importance ranking accelerates recovery, thereby improving the resilience of ICIs.

This paper presents first an ontology of risk for interdependent and heterogeneous Critical Infrastructures (CIs). It defines a data structure called Service Quality Descriptor (SQD) specifying the degradation of QoS over time, which should be shared between interconnected CI. SQD are shared in real time and contain a precise prediction of the future quality of service, so that this sharing can be useful to avoid failures, identify interdependencies, or accelerate and coordinate power failure recoveries and service restoration. Finally, the paper proposes a simplified method to determine the SQD of a delivery service as a linear function of the SQD of supporting services and parameters depending on the service delivery infrastructure. The approach has been defined within the European FP-7 project MICIE, in line with the EU initiative to establish a Critical Infrastructure Warning Information Network (CIWIN).KeywordsRisk analysisSecurity Quality DescriptorQuality of ServiceRisk ontologyInterdependency riskCritical infrastructure ProtectionRisk Level

The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI) such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN) modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.

The presented ongoing research project focuses on the challenges concerning the protection of critical infrastructures. Since critical infrastructures become more and more cross-linked a single breakdown can cause serious cascading effects on other infrastructures. Interdependencies of critical infrastructures are boundaryspanning and therefore public authorities, operating companies and other stakeholders (e.g. German Federal Agency for technical relief, Red Cross) as well as stakeholders of neighbouring states must have access to a solution which enables the urgently needed cooperation of all parties involved. The aim of the project is to develop an online platform to facilitate knowledge exchange among stakeholders, an online tool to analyse the interdependencies and to design a sustainable and effective knowledge management. This platform will allow registered members to find and make use of the information about the stakeholders and their competencies concerning the protection of critical infrastructures.

When we examine the impacts of space weather on society, do we really understand the risks? Can past experiences reliably predict what will happen in the future? As the complexity of technology increases, there is the potential for it to become more fragile, allowing for a single point of failure to bring down the entire system. Take the Global Positioning System (GPS) as an example. GPS positioning, navigation, and timing have become an integral part of daily life, supporting transportation and communications systems vital to the aviation, merchant marine, cargo, cellular phone, surveying, and oil exploration industries. Everyday activities such as banking, mobile phone operations, and even the control of power grids are facilitated by the accurate timing provided by GPS. Understanding the risks of space weather to GPS and the many economic sectors reliant upon it, as well as how to build resilience, was the focus of a policy workshop organized by the American Meteorological Society (AMS) and held on 13–14 October 2010 in Washington, D. C. The workshop brought together a select group of policy makers, space weather scientists, and GPS experts and users. Arif Alikhan, assistant secretary for policy development in the U.S. Department of Homeland Security, kicked off the meeting by stressing that authorities should see GPS and resilience through an all-hazards lens rather than plan for each emergency scenario on a case-by-case basis. Whether a GPS signal error or disruption is caused by a solar storm, an intentional jammer, or some other source, government and industries need to plan to respond to the incident and restore capability as quickly as possible, although, Alikhan remarked, “The number of potential scenarios is infinite, and we have neither the time nor resources to plan against them.” Alikhan suggested that risk managers conceptualize the scope of critical assets in need of protecting through a resilience and risk analysis framework. He recommended that decision makers take an inventory of all functions provided for by their institutions“ use of GPS. Next, through risk-informed prioritization, planners can ascertain whether a backup is really needed for any services provided by GPS. “In this fiscal environment,” Alikhan said, “we will need to shrink the haystack, or size of the problem, in order to be effective.” Because the interdependencies of critical infrastructures are not fully appreciated by the public and private sectors, he stressed that a mix of governmental, commercial, and international stakeholders should develop plans and procedures to make systems more resilient. The remainder of the workshop was organized around discussions in three sessions: (1) identifying the vulnerability of GPS technologies and services to space weather, (2) identifying how this vulnerability affects users who depend on GPS, and (3) developing opportunities and policies for building resilience. In the first session, participants agreed that the vulnerability of GPS needs to be defined for different segments (e.g., satellites, signals, users). While some understanding of user needs exists, the definition of user requirements needs more clarification because space weather events will affect some technologies more than others. Also, a threat assessment would be valuable to best understand how severe the impacts might be and what mitigation options are available. With the recent news that Google™ is building self-driving robotic cars that depend on GPS, trying to capture possible future vulnerabilities is extremely challenging. During a debate on how much to stress the impact of a solar flare as massive as the 1859 Carrington event, many warned that while the public should be made aware of such a potential occurrence, it should not govern planning, since such a doomsday scenario is uncertain and expected to happen only very infrequently. When discussing in the second session how users of GPS are affected, participants discovered that communicating with GPS stakeholders and users is a challenge because many do not understand the impacts of adverse space weather. In particular, many of the service providers and end users of GPS were not in business during the previous solar maximum and therefore are not familiar with space weather hazards. To help remedy this, outreach approaches were discussed, and some participants argued that the space weather community should anticipate the needs of the users. Others instead urged the space weather community to deal only with the service providers—not end users—and ask them rather than tell them what they need. Despite this debate, there was broad agreement that space weather researchers should develop better measurements and predictions of the ionosphere. In addition, participants agreed that scintillation specifications and predictions would be useful to many users of GPS. Improved predictions would be possible by installing more dual-frequency stations and scintillation monitors, they noted. The workshop concluded with a discussion of policy options for building resilience. Participants debated what measures could be taken, such as developing new policies, investing in research and development, changing industry practices, and public and private sector collaboration. Scott Pace, director of George Washington University“s Space Policy Institute, stressed in his presentation that stakeholders and disaster planners should focus on three aspects: prediction, detection, and mitigation. Better space physics/heliophysics science is needed, and it was recommended that this be a top priority for the Solar and Space Physics decadal survey, which sets future nationwide research targets and is currently under review by the U.S. National Research Council. Findings and recommendations from the workshop will be published in a report by AMS. The results will be widely distributed to various stakeholders, including policy makers, GPS service providers, federal agencies, research communities, and international organizations. Genene Fisher is a senior policy fellow in the American Meteorological Society's Policy Program. E-mail: [email protected]

Recent adversarial incidents highlight the inherent vulnerabilities in multiple targeted critical infrastructures cyber-physical systems. Next-Gen critical infrastructures will continue evolving to be more distributed, inter-connected, and interdependent. Significant negative consequences could be inflected by threat actors exploiting those characteristics, requiring a more comprehensive and systematic approach. This work proposes a data-based hierarchical framework to identify, detect, and mitigate cyber and/or physical attacks through enriched dynamic situational awareness encompassing individual and interdependent critical infrastructures.

This paper presents a novel approach to the critical infrastructure (CI) interdependencies analysis, based on the Dynamic Bayesian Network (DBN) formalism. Our original modeling procedure divides the DBN in three levels: an atomic events level, which models the adverse events impacting on the analyzed CIs, a propagation level, which captures CI interdependencies, and a services level, which allows to monitor the state of provided services. Three types of analyses can be performed: a reliability study, an adverse events propagation study, and a failure identification analysis. A case study provided by Israel Electric Corporation is considered, and explicative simulations are presented and discussed in detail.

The failure of urban Electrical Distribution Systems (EDSs) can lead to direct or indirect consequences for their interdependent critical infrastructures, for example, the hospitals, the fire department, etc., negatively affecting the well-being of citizens in the city. To improve the resilience of the coupled power network, the Operational Interdependence Simulator (OIS) is proposed to help prioritize the queue of failure recovery and Minimum Spanning Tree and Shortest Path Tree topology reconfiguration to minimize critical load downtime. Additionally, AI agents are introduced to assist decision-making processes. By utilizing machine learning and training in thousands of offline scenarios, the system can be used for real-time calculation of the optimal recovery paths when given the number and location of electrical faults. The IEEE 70-node distribution system case validated the high prediction accuracy and post-disaster topology reconfiguration while considering the interdependencies.

Although various aspects of interdependencies among Power, Water, and Gas (PWG) infrastructures have been studied in the last couple of decades, there still exists void of modeling techniques capable of revealing the interdependencies among real-world infrastructures. This paper presents review of the state-of-the-art knowledge on interdependent critical infrastructure (ICI) modeling techniques along with delineation and discussion of interdependencies at transmission and distribution levels among PWG networks. The present study will also outline the suitability of various approaches to work with real-time infrastructure monitoring data that is becoming abundantly available in the recent years. The paper also highlights some directions on future research in interdependency modeling as well as suggestions on improving real-time interdependent models in operational and physical aspects.

Sustainable transport commonly considers either the interaction between built and natural environments or the interface between transportation and interdependent critical infrastructure. Although considering each of these key dimensions is a crucial task for achieving sustainable transport, the dimensions are infrequently considered together. When an integrated network design framework is proposed, two important issues are taken into account: ( a) the aftermath of potential severe weather episodes on metropolitan-area infrastructure and ( b) the existing interdependencies across transportation and fuel supply chain networks. Then the response of infrastructure in the face of flooding hazards is investigated. Framed within a multistage linear stochastic program, the proposed model seeks to find fueling station deployment that provides the transportation network with optimum random functionality when the network is stressed or under attack. A set of numerical experiments illustrates how changes to enhancement strategies at different stages of government affect the optimal investments in resilient design.

Many of the current traditional system engineering (TSE) approaches for elicitation of requirements are insufficient when deployed in complex situations. TSE approach to requirement elicitation is based on assumption of stable environmental conditions. However, the elicitation of requirements for complex systems (i.e., interdependent critical infrastructures) requires innovative approaches that should go beyond technical aspects of a situation. Complex situations arise when multiple complex infrastructures interdependently interact to provide goods and services for public health and safety. The elicitation of requirements for such a system must consider the nature of system of interest, its environment and system observer. On this backdrop, this paper reviews complexity associated with attained requirements for complex infrastructures, failures and provides an overview of a proposed high-level framework for infrastructure requirement elicitation.

Contemporary wars generate profound and long‑lasting effects on the environment, extending beyond the immediate sphere of material and humanitarian destruction. This article examines the consequences of zonal wars on the environment through four complementary perspectives: legal, ecological, socio‑economic, and ethical. Modern warfare produces extensive pollution of soil, air, and water, destroys natural habitats, and causes irreversible losses of biodiversity. Although the analysis includes comparative references to conflicts in various regions, particular attention is focused on the war in Ukraine, which is considered especially relevant due to its unfolding within contemporary Europe and its geographical proximity to Romania and other states in the region. The war in Ukraine allows for a concrete assessment of the ways in which modern military actions affect natural ecosystems, through pollution, habitat destruction, and the disruption of biodiversity, generate new legal challenges regarding environmental protection in the context of armed conflict, raise ethical dilemmas concerning the responsibility of the actors involved, and produce economic and social imbalances in neighboring states. In this context, the article also addresses the concept of ecocide, analyzed as a potential new legal category intended to sanction deliberate and severe environmental destruction in situations of armed conflict. Through an interdisciplinary approach, the article seeks to highlight the need to strengthen the international normative framework and regional cooperation in order to prevent and mitigate the environmental effects of wars conducted in areas characterized by high population density and interdependent critical infrastructures.

The chapter engages in exploring possibilities of innovation and use of future technology arising from multistakeholder collaboration in essential societal functions such as public services, critical infrastructure systems and public policy arena. Multistakeholder collaboration is the key to adaptation and resilience amidst the fast-changing twenty-first century world around us. Owing to increased interconnectedness and interdependencies of complex socio-technical systems, critical infrastructures and essential services, our socio-technical relationships have also grown more complex. On one hand, the tightly coupled systems, services and infrastructures are highly optimized while on the other, because of their high optimization and tightly coupled nature, these systems are often more prone to catastrophic disruptions and crises. So, what is the way forward to effectively increase adaptation and resilience? The chapter engages in the discussion of boundary spanning activities such as the essential public services where multistakeholder collaboration among various actors, i.e., public, private, academia and the industry is inevitable due to cross-cutting issues, demands and challenges. With examples of successful cases and evidence from scientific literature, the chapter makes a convincing case in favour of multistakeholder collaboration as a powerful tool to raise societal resilience.KeywordsMultistakeholder collaborationInnovationSocio-technical systemsCrisis managementDigitalization

Much of Critical Infrastructure (CI) interdependency research focuses on short-term cascading effects from catastrophic incidents. These relationships are most often modeled in a direct physical sense, for example, a flooded road blocking emergency vehicle response. The relationship between economic investment and degradation in CIs, however, remains an under-explored research area. Focusing on three CIs---transportation, public utilities, and communications---this paper presents a system dynamics approach to modeling degradation and infrastructure investment. Combining traditional physical and cyber approaches to infrastructure modeling with a human factors component, we present a methodology for quantifying degradation of interdependent CIs. The model shows some of the dangerous feedback cycles of degradation that can occur between infrastructures when investment and social resiliency are insufficient. The purpose of this paper is to develop a method to incorporate social systems into interdependent infrastructure research that can be built into a tool to aid policymakers in understanding and addressing investment linkages between CIs.