Security and Survivability of Large Scale Critical Infrastructures

2002 ◽  
pp. 84-85 ◽  
Author(s):  
John Bigham
Keyword(s):  
Large Scale ◽  
Critical Infrastructures

scholarly journals Network isolators inhibit failure spreading in complex networks

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Franz Kaiser ◽  
Vito Latora ◽  
Dirk Witthaut
Keyword(s):  
Complex Networks ◽  
Large Scale ◽  
Power Transmission ◽  
Power Grids ◽  
Cascading Failure ◽  
Critical Infrastructures ◽  
Daily Lives ◽  
Supply Networks ◽  
Water Transmission ◽  
Complete Collapse

AbstractIn our daily lives, we rely on the proper functioning of supply networks, from power grids to water transmission systems. A single failure in these critical infrastructures can lead to a complete collapse through a cascading failure mechanism. Counteracting strategies are thus heavily sought after. In this article, we introduce a general framework to analyse the spreading of failures in complex networks and demostrate that not only decreasing but also increasing the connectivity of the network can be an effective method to contain damages. We rigorously prove the existence of certain subgraphs, called network isolators, that can completely inhibit any failure spreading, and we show how to create such isolators in synthetic and real-world networks. The addition of selected links can thus prevent large scale outages as demonstrated for power transmission grids.

Synthetic Environments for Investigating Collaborative Information Seeking: An Application in Emergency Restoration of Critical Infrastructures

2015 ◽  
Vol 12 (3) ◽  
Author(s):  
David Mendonça ◽  
William A. Wallace ◽  
Barbara Cutler ◽  
James Brooks
Keyword(s):  
Information Seeking ◽  
Large Scale ◽  
Critical Infrastructure ◽  
Future Research ◽  
Critical Infrastructures ◽  
Close Collaboration ◽  
Number Of Factors ◽  
Computer Based ◽  
Collaborative Information Seeking ◽  
Post Disaster

AbstractLarge-scale disasters can produce profound disruptions in the fabric of interdependent critical infrastructure systems such as water, telecommunications and electric power. The work of post-disaster infrastructure restoration typically requires information sharing and close collaboration across these sectors; yet – due to a number of factors – the means to investigate decision making phenomena associated with these activities are limited. This paper motivates and describes the design and implementation of a computer-based synthetic environment for investigating collaborative information seeking in the performance of a (simulated) infrastructure restoration task. The main contributions of this work are twofold. First, it develops a set of theoretically grounded measures of collaborative information seeking processes and embeds them within a computer-based system. Second, it suggests how these data may be organized and modeled to yield insights into information seeking processes in the performance of a complex, collaborative task. The paper concludes with a discussion of implications of this work for practice and for future research.

scholarly journals Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Yunpeng Wang ◽  
Yuqin Feng ◽  
Wenxiang Li ◽  
William Case Fulcher ◽  
Li Zhang
Keyword(s):  
Road Network ◽  
Large Scale ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Critical Infrastructures ◽  
Traffic Demand ◽  
The Road ◽  
Utility Index ◽  
Decision Supporting ◽  
Improved Ant Colony Algorithm

We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.

scholarly journals TEXAS 2050

2016 ◽  
Author(s):  
Ian Caine ◽  
◽  
Trenton Tunks ◽  
Carlos Serrano ◽  
◽  
...  
Keyword(s):  
United States ◽  
Large Scale ◽  
The United States ◽  
Critical Infrastructures ◽  
Territorial Expansion ◽  
United States Population ◽  
Regional Plan ◽  
The U.S ◽  
Critical Link ◽  
Increasing Efficiencies

By the year 2050 the United States population will increase by half, with 70% living in a megaregion (Regional Plan Association, 2006). These numbers emphasize the critical link between large-scale territorial expansion and the prospects for successful urbanism. Currently, 11 mega-regions exist in the U.S., each bound together by a unique mixture of demographics, infrastructure, culture, and environment. As each megaregion grows, it must identify and leverage critical infrastructures that are capable of binding geographies and increasing efficiencies. This project speculates about one such strategy for the emerging megaregion known as the Texas Triangle.

scholarly journals HARCI-EU, a harmonized gridded dataset of critical infrastructures in Europe for large-scale risk assessments

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Filipe Batista e Silva ◽  
Giovanni Forzieri ◽  
Mario Alberto Marin Herrera ◽  
Alessandra Bianchi ◽  
Carlo Lavalle ◽  
...  
Keyword(s):  
Large Scale ◽  
Risk Assessments ◽  
Critical Infrastructures ◽  
Gridded Dataset

Fault-Tree Analysis for Power Gird Emergency Logistics System under Large-Scale Natural Disaster

2014 ◽  
Vol 986-987 ◽  
pp. 311-314
Author(s):  
Feng Yu ◽  
Xiang Yang Li ◽  
Guo Jun Yue
Keyword(s):  
Natural Disaster ◽  
Large Scale ◽  
Risk Estimation ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Critical Infrastructures ◽  
Logistics System ◽  
Tree Analysis ◽  
Emergency Logistics ◽  
Vital Component

Power grid, one of the critical infrastructures, is a vital component of the world’s energy supply. Once large-scale natural disaster occurs, it is inevitable to meet unexpected faults on emergency logistic. Fault-tree analysis (FTA) is a risk estimation tool to describe and model causal interactions and logical relationships between undesired events in a system Taking uncertain situation and response failure into consideration, this paper proposed a fault-tree analysis on PG-ELS with fuzzy probabilistic confidence. The most critical failure mode is identified using the ranking method based on interval number.

scholarly journals Identifying and Analyzing Dependencies in and among Complex Cyber Physical Systems

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1685
Author(s):  
Aida Akbarzadeh ◽  
Sokratis Katsikas
Keyword(s):  
Complex System ◽  
Large Scale ◽  
Graphical Model ◽  
Cyber Physical Systems ◽  
Critical Infrastructures ◽  
Valuable Insight ◽  
Physical Systems ◽  
Dependency Structure ◽  
Tightly Coupled ◽  
Insight Into

Contemporary Critical Infrastructures (CIs), such as the power grid, comprise cyber physical systems that are tightly coupled, to form a complex system of interconnected components with interacting dependencies. Modelling methodologies have been suggested as proper tools to provide better insight into the dependencies and behavioural characteristics of these complex systems. In order to facilitate the study of interconnections in and among critical infrastructures, and to provide a clear view of the interdependencies among their cyber and physical components, this paper proposes a novel method, based on a graphical model called Modified Dependency Structure Matrix (MDSM). The MDSM provides a compact perspective of both inter-dependency and intra-dependency between subsystems of one complex system or two distinct systems. Additionally, we propose four parameters that allow the quantitative assessment of the characteristics of dependencies, including multi-order dependencies in large scale CIs. We illustrate the workings of the proposed method by applying it to a micro-distribution network based on the G2ELAB 14-Bus model. The results provide valuable insight into the dependencies among the network components and substantiate the applicability of the proposed method for analyzing large scale cyber physical systems.

scholarly journals Resilience in interorganizational networks: dealing with day-to-day disruptions in critical infrastructures

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mitchell J. van den Adel ◽  
Thomas A. de Vries ◽  
Dirk Pieter van Donk
Keyword(s):  
Information Exchange ◽  
Large Scale ◽  
Critical Infrastructures ◽  
Supply Network ◽  
Interorganizational Network ◽  
Supply Networks ◽  
Content Type ◽  
Essential Services ◽  
Boundary Information ◽  
Practical Implications

Purpose Critical infrastructures (CIs) for essential services such as water supply and electricity delivery are notoriously vulnerable to disruptions. While extant literature offers important insights into the resilience of CIs following large-scale disasters, our understanding of CI resilience to the more typical disruptions that affect CIs on a day-to-day basis remains limited. The present study investigates how the interorganizational (supply) network that uses and manages the CI can mitigate the adverse consequences of day-to-day disruptions. Design/methodology/approach Longitudinal archival data on 277 day-to-day disruptions within the Dutch national railway CI were collected and analyzed using generalized estimating equations. Findings The empirical results largely support the study’s predictions that day-to-day disruptions have greater adverse effects if they co-occur or are relatively unprecedented. The findings further show that the involved interorganizational network can enhance CI resilience to these disruptions, in particular, by increasing the overall level of cross-boundary information exchange between organizations inside the network. Practical implications This study helps managers to make well-informed choices regarding the target and intensity of their cross-boundary information-exchange efforts when dealing with day-to-day disruptions affecting their CI. The findings illustrate the importance of targeting cross-boundary information exchange at the complete interorganizational network responsible for the CI and to increase the intensity of such efforts when CI disruptions co-occur and/or are unprecedented. Originality/value This study contributes to our academic understanding of how network-level processes (i.e. cross-boundary information exchange) can be managed to ensure interorganizational (supply) networks’ resilience to day-to-day disruptions in a CI context. Subsequent research may draw from the conceptual framework advanced in the present study for examining additional supply network-level processes that can influence the effectiveness of entire supply networks. As such, the present research may assist scholars to move beyond a simple dyadic context and toward examining complete supply networks

scholarly journals Integrating Resilience in Time-based Dependency Analysis: A Large-Scale Case Study for Urban Critical Infrastructures

2021 ◽  
Author(s):  
Vittorio Rosato ◽  
Antonio Di Pietro ◽  
Panayiotis Kotzanikolaou ◽  
George Stergiopoulos ◽  
Giulio Smedile
Keyword(s):  
Large Scale ◽  
Critical Infrastructures ◽  
Quality Level ◽  
Dependency Analysis ◽  
Analysis Methodology ◽  
Emergency Managers ◽  
Risk Forecast ◽  
Critical Paths ◽  
Real Scenario ◽  
Overall Risk

As critical systems shall withstand different types of perturbations affecting their functionalities and their service level, resilience is a very important requirement. Especially in an urban critical infrastructures where the occurrence of natural events may influence the state of other dependent infrastructures from various different sectors, the overall resilience of such infrastructures against large scale failures is even more important. When a perturbation occurs in a system, the quality (level) of the service provided by the affected system will be reduced and a recovery phase will be triggered to restore the system to its normal operation level. According to the implemented recovery controls, the restoration phase may follow a different growth model. This paper extends a previous time-based dependency risk analysis methodology by integrating and assessing the effect of recovery controls. The main goal is to dynamically assess the evolution of recovery over time, in order to identify how the expected recovery plans will eventually affect the overall risk of the critical paths. The proposed recovery-aware time-based dependency analysis methodology was integrated into the CIPCast Decision Support System that enables risk forecast due to natural events to identify vulnerable and disrupted assets (e.g., electric substations, telecommunication components) and measure the expected risk paths. Thus, CIPCast can be valuable to Critical Infrastructure Operators and other Emergency Managers involved in a crisis assessment to evaluate the effect of natural and anthropic threats affecting critical assets and plan proper countermeasures to reduce the overall risk of degradation of services. The proposed methodology is evaluated in a real scenario, which utilizes several infrastructures and Points of Interest of the city of Rome.

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