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| @article{Kelly:2016, | ||
| title = {Integrated Infrastructure: [C]yber Resiliency in Society, Mapping the Consequences of an Interconnected Digital Economy}, | ||
| journal = {}, | ||
| volume = {}, | ||
| pages = {}, | ||
| year = {2016}, | ||
| issn = {}, | ||
| doi = {}, | ||
| url = {https://www.jbs.cam.ac.uk/wp-content/uploads/2020/08/crs-integrated-infrastructure-cyber-resiliency-in-society.pdf}, | ||
| author = {{Kelly}, S. and {Leverett}, E. and {Oughton}, E.~J. and {Copic}, J. and {Thacker}, S. and {Pant}, R. and {Pryor}, L. and {Kassara}, G. and {Evan}, T. and {Ruffle}, S. and {Tuveson}, M. and {Coburn}, A. and {Ralph}, D. and {Hall}, J.}, | ||
| } | ||
| @article{Oughton:2019, | ||
| title = {Stochastic Counterfactual Risk Analysis for the Vulnerability Assessment of Cyber-Physical Attacks on Electricity Distribution Infrastructure Networks}, | ||
| journal = {Risk Analysis}, | ||
| pages = {2012 – 2031}, | ||
| year = {2019}, | ||
| issn = {1539-6924}, | ||
| doi = {https://doi.org/10.1111/risa.13291}, | ||
| url = {https://onlinelibrary.wiley.com/doi/full/10.1111/risa.13291}, | ||
| author = {{Oughton}, E.~J. and {Ralph}, D. and {Pant}, R. and {Leverett}, E. and {Copic}, J. and {Thacker}, S. and {Dada}, R. and {Ruffle}, S. and {Tuveson}, M. and {Hall}, J.}, | ||
| } | ||
| @article{Zorn:2016, | ||
| title = {Quantifying Directional Dependencies from Infrastructure Restoration Data}, | ||
| journal = {Earthquake Spectra}, | ||
| pages = {1363–1381}, | ||
| year = {2016}, | ||
| issn = {1539-6924}, | ||
| doi = {https://doi.org/10.1193/013015EQS015M}, | ||
| url = {https://journals.sagepub.com/doi/full/10.1193/013015EQS015M}, | ||
| author = {{Zorn}, C.~R. and {Shamseldin}, A.~Y.}, | ||
| } | ||
| @article{Oughton:2018, | ||
| title = {The Economic Impact of Critical National Infrastructure Failure Due to Space Weather}, | ||
| journal = {Oxford Research Encyclopedia of Natural Hazard Science}, | ||
| pages = {}, | ||
| year = {2018}, | ||
| issn = {}, | ||
| doi = {https://doi.org/10.1093/acrefore/9780199389407.013.315}, | ||
| url = {https://oxfordre.com/naturalhazardscience/view/10.1093/acrefore/9780199389407.001.0001/acrefore-9780199389407-e-315}, | ||
| author = {{Oughton}, E.~J.}, | ||
| } | ||
| @article{Hickford:2018, | ||
| title = {Resilience engineering: theory and practice in interdependent infrastructure systems}, | ||
| journal = {Environment Systems and Decisions}, | ||
| pages = {278–291}, | ||
| year = {2018}, | ||
| issn = {2194-5411}, | ||
| doi = {https://doi.org/10.1007/s10669-018-9707-4}, | ||
| url = {https://link.springer.com/article/10.1007/s10669-018-9707-4}, | ||
| author = {{Hickford}, A.~J. and {Blainey}, S.~P. and {Ortega Hortelano}, A. and {Pant}, R.}, | ||
| @article{pant_critical_2017, | ||
| title = {Critical infrastructure impact assessment due to flood exposure}, | ||
| issn = {1753-318X}, | ||
| url = {http://onlinelibrary.wiley.com/doi/10.1111/jfr3.12288/abstract}, | ||
| doi = {10.1111/jfr3.12288}, | ||
| abstract = {Critical national infrastructures, including energy, transport, digital communications, and water, are prone to flood damage. Their geographical extent is a determinant of, and is determined by, patterns of human development, which is often concentrated in floodplains. It is important to understand how infrastructure systems react to large-scale flooding. In this paper, we present an integrated framework for critical infrastructure flood impact assessment. Within this integrated framework, we represent interdependent infrastructure assets through spatial network models. We quantify infrastructure flood impacts in terms of disrupted customers linked directly to flood assets and customers disrupted indirectly due to network effects. The analysis shows how spatial network models inform flood risk management practitioners to identify and compare critical infrastructures risks on flooded and non-flooded land, for prioritising flood protection investments and improve resilience of cities. A case study of the Thames catchment in England is presented, which contains key infrastructure assets and highest population concentrations in United Kingdom.}, | ||
| language = {en}, | ||
| urldate = {2017-10-29}, | ||
| journal = {Journal of Flood Risk Management}, | ||
| author = {Pant, R. and Thacker, S. and Hall, J.w. and Alderson, D. and Barr, S.}, | ||
| month = jan, | ||
| year = {2017}, | ||
| keywords = {Critical infrastructures, customer disruptions, flood catchment, flood hazard, infrastructure networks, risks, vulnerability}, | ||
| pages = {n/a--n/a}, | ||
| file = {Snapshot:C\:\\Users\\edwar\\Zotero\\storage\\AAZFYCQW\\abstract.html:text/html} | ||
| } | ||
|
|
||
| @techreport{kelly_integrated_2016, | ||
| address = {Cambridge}, | ||
| title = {Integrated {Infrastructure}: {Cyber} {Resiliency} in {Society}, {Mapping} the {Consequences} of an {Interconnected} {Digital} {Economy}}, | ||
| url = {https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjI_NOwpr_RAhXFPxoKHaSPBO4QFggcMAA&url=http%3A%2F%2Fcambridgeriskframework.com%2Fgetdocument%2F40&usg=AFQjCNHos7tFzfHuEFLpHT1H-f-bB9SmTg&sig2=-hXbO96P4cuWWDYgN_XkQQ}, | ||
| institution = {Cambridge Centre for Risk Studies}, | ||
| author = {Kelly, S. and Leverett, E. and Oughton, E.J. and Copic, J. and Thacker, S. and Pant, R. and Pryor, L. and Kassara, G. and Evan, T. and Ruffle, S. J. and Tuveson, M. and Coburn, A. W. and Ralph, D. and Hall, J. W.}, | ||
| year = {2016} | ||
| } | ||
|
|
||
| @article{hall_strategic_2016, | ||
| title = {Strategic analysis of the future of national infrastructure}, | ||
| issn = {0965-089X}, | ||
| url = {http://www.icevirtuallibrary.com/doi/10.1680/jcien.16.00018}, | ||
| doi = {10.1680/jcien.16.00018}, | ||
| abstract = {There have been many calls for a more strategic, long-term approach to national infrastructure in the UK and elsewhere around the world. While appealing in principle, developing a national infrastructure strategy in practice poses major challenges of complexity and uncertainty. The UK Infrastructure Transitions Research Consortium has set out a systematic methodology for long-term analysis of the performance of national infrastructure systems. It deals with each infrastructure sector – energy, transport, digital communications, water supply, waste water, flood protection and solid waste – in a consistent framework and assesses the interdependencies between sectors. The method is supported with the world’s first infrastructure ‘system-of-systems’ model, which has been developed for long-term decision analysis in interdependent infrastructure systems. This paper presents the Nismod model’s analysis in the National Needs Assessment report launched at the Institution of Civil Engineers in October 2016.}, | ||
| urldate = {2016-11-26}, | ||
| journal = {Proceedings of the Institution of Civil Engineers - Civil Engineering}, | ||
| author = {Hall, Jim W. and Thacker, Scott and Ives, Matt C. and Cao, Yue and Chaudry, Modassar and Blainey, Simon P. and Oughton, Edward J.}, | ||
| month = nov, | ||
| year = {2016}, | ||
| pages = {1--9}, | ||
| file = {Snapshot:C\:\\Users\\edwar\\Zotero\\storage\\6RFFGUH6\\jcien.16.html:text/html} | ||
| } | ||
|
|
||
| @article{oughton_strategic_2018, | ||
| title = {The strategic national infrastructure assessment of digital communications}, | ||
| volume = {20}, | ||
| issn = {2398-5038}, | ||
| url = {https://www.emeraldinsight.com/doi/abs/10.1108/DPRG-02-2018-0004}, | ||
| doi = {10.1108/DPRG-02-2018-0004}, | ||
| number = {3}, | ||
| urldate = {2018-07-11}, | ||
| journal = {Digital Policy, Regulation and Governance}, | ||
| author = {Oughton, E.J. and Frias, Z. and Dohler, M. and Whalley, J. and Sicker, D. and Hall, J.W. and Crowcroft, J. and Cleevely, D.D.}, | ||
| month = mar, | ||
| year = {2018}, | ||
| pages = {197--210}, | ||
| file = {Snapshot:C\:\\Users\\edwar\\Zotero\\storage\\IAL9XPYK\\DPRG-02-2018-0004.html:text/html} | ||
| } | ||
|
|
||
| @article{oughton_economic_2018, | ||
| title = {The {Economic} {Impact} of {Critical} {National} {Infrastructure} {Failure} {Due} to {Space} {Weather}}, | ||
| url = {http://oxfordre.com/view/10.1093/acrefore/9780199389407.001.0001/acrefore-9780199389407-e-315}, | ||
| doi = {10.1093/acrefore/9780199389407.013.315}, | ||
| abstract = {Space weather is a collective term for different solar or space phenomena that can detrimentally affect technology. However, current understanding of space weather hazards is still relatively embryonic in comparison to terrestrial natural hazards such as hurricanes, earthquakes, or tsunamis. Indeed, certain types of space weather such as large Coronal Mass Ejections (CMEs) are an archetypal example of a low-probability, high-severity hazard. Few major events, short time-series data, and the lack of consensus regarding the potential impacts on critical infrastructure have hampered the economic impact assessment of space weather. Yet, space weather has the potential to disrupt a wide range of Critical National Infrastructure (CNI) systems including electricity transmission, satellite communications and positioning, aviation, and rail transportation.In the early 21st century, there has been growing interest in these potential economic and societal impacts. Estimates range from millions of dollars of equipment damage from the Quebec 1989 event, to some analysts asserting that losses will be in the billions of dollars in the wider economy from potential future disaster scenarios. Hence, the origin and development of the socioeconomic evaluation of space weather is tracked, from 1989 to 2017, and future research directions for the field are articulated. Since 1989, many economic analyzes of space weather hazards have often completely overlooked the physical impacts on infrastructure assets and the topology of different infrastructure networks. Moreover, too many studies have relied on qualitative assumptions about the vulnerability of CNI. By modeling both the vulnerability of critical infrastructure and the socioeconomic impacts of failure, the total potential impacts of space weather can be estimated, providing vital information for decision makers in government and industry.Efforts on this subject have historically been relatively piecemeal, which has led to little exploration of model sensitivities, particularly in relation to different assumption sets about infrastructure failure and restoration. Improvements may be expedited in this research area by open-sourcing model code, increasing the existing level of data sharing, and improving multidisciplinary research collaborations between scientists, engineers, and economists.}, | ||
| language = {en}, | ||
| urldate = {2018-12-31}, | ||
| journal = {Oxford Research Encyclopedia of Natural Hazard Science}, | ||
| author = {Oughton, E.J.}, | ||
| month = nov, | ||
| year = {2018}, | ||
| file = {Snapshot:C\:\\Users\\edwar\\Zotero\\storage\\RUYM6CK8\\acrefore-9780199389407-e-315.html:text/html} | ||
| } | ||
|
|
||
| @article{oughton_stochastic_2019, | ||
| title = {Stochastic {Counterfactual} {Risk} {Analysis} for the {Vulnerability} {Assessment} of {Cyber}-{Physical} {Attacks} on {Electricity} {Distribution} {Infrastructure} {Networks}}, | ||
| volume = {39}, | ||
| copyright = {© 2019 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.}, | ||
| issn = {1539-6924}, | ||
| url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/risa.13291}, | ||
| doi = {10.1111/risa.13291}, | ||
| abstract = {In December 2015, a cyber-physical attack took place on the Ukrainian electricity distribution network. This is regarded as one of the first cyber-physical attacks on electricity infrastructure to have led to a substantial power outage and is illustrative of the increasing vulnerability of Critical National Infrastructure to this type of malicious activity. Few data points, coupled with the rapid emergence of cyber phenomena, has held back the development of resilience analytics of cyber-physical attacks, relative to many other threats. We propose to overcome data limitations by applying stochastic counterfactual risk analysis as part of a new vulnerability assessment framework. The method is developed in the context of the direct and indirect socioeconomic impacts of a Ukrainian-style cyber-physical attack taking place on the electricity distribution network serving London and its surrounding regions. A key finding is that if decision-makers wish to mitigate major population disruptions, then they must invest resources more-or-less equally across all substations, to prevent the scaling of a cyber-physical attack. However, there are some substations associated with higher economic value due to their support of other Critical National Infrastructures assets, which justifies the allocation of additional cyber security investment to reduce the chance of cascading failure. Further cyber-physical vulnerability research must address the tradeoffs inherent in a system made up of multiple institutions with different strategic risk mitigation objectives and metrics of value, such as governments, infrastructure operators, and commercial consumers of infrastructure services.}, | ||
| language = {en}, | ||
| number = {9}, | ||
| urldate = {2019-09-09}, | ||
| journal = {Risk Analysis}, | ||
| author = {Oughton, Edward J. and Ralph, Daniel and Pant, Raghav and Leverett, Eireann and Copic, Jennifer and Thacker, Scott and Dada, Rabia and Ruffle, Simon and Tuveson, Michelle and Hall, Jim W.}, | ||
| year = {2019}, | ||
| keywords = {Critical National Infrastructure, cyber-physical attack, infrastructure}, | ||
| pages = {2012--2031}, | ||
| file = {Snapshot:C\:\\Users\\edwar\\Zotero\\storage\\8KCWJXFJ\\risa.html:text/html} | ||
| } | ||
|
|
||
| @article{zorn_quantifying_2016, | ||
| title = {Quantifying {Directional} {Dependencies} from {Infrastructure} {Restoration} {Data}}, | ||
| volume = {32}, | ||
| issn = {8755-2930}, | ||
| url = {https://doi.org/10.1193/013015EQS015M}, | ||
| doi = {10.1193/013015EQS015M}, | ||
| abstract = {Lifeline utilities and critical infrastructures are becoming increasingly interactive and dependent on one another for normal operation. With a natural disaster or disruptive event, these dependencies can be studied under stressed conditions. To replicate events and inform future simulations, such dependencies can be quantified in both magnitude and direction. This paper builds on recent efforts by proposing a new dependency index methodology that gives importance to the direction of dependency between coupled infrastructures and equally weighting the multiple dependencies that may be realized across a variety of lag times. The effectiveness of this methodology is presented as a case study for the 22 February 2011 earthquake experienced in Christchurch, New Zealand. Dependencies are quantified for a range of critical infrastructure couplings, which provide insight into the future application of these results and the requirement for integration with qualitative studies to accurately inform interdependency models.}, | ||
| language = {en}, | ||
| number = {3}, | ||
| urldate = {2021-01-06}, | ||
| journal = {Earthquake Spectra}, | ||
| author = {Zorn, Conrad R. and Shamseldin, Asaad Y.}, | ||
| month = aug, | ||
| year = {2016}, | ||
| note = {Publisher: SAGE Publications Ltd STM}, | ||
| pages = {1363--1381}, | ||
| file = {SAGE PDF Full Text:C\:\\Users\\edwar\\Zotero\\storage\\U8V45XL3\\Zorn and Shamseldin - 2016 - Quantifying Directional Dependencies from Infrastr.pdf:application/pdf} | ||
| } | ||
|
|
||
| @article{hickford_resilience_2018, | ||
| title = {Resilience engineering: theory and practice in interdependent infrastructure systems}, | ||
| volume = {38}, | ||
| issn = {2194-5411}, | ||
| shorttitle = {Resilience engineering}, | ||
| url = {https://doi.org/10.1007/s10669-018-9707-4}, | ||
| doi = {10.1007/s10669-018-9707-4}, | ||
| abstract = {The economy and well-being of modern societies relies on complex and interdependent infrastructure systems to enable delivery of utilities and movement of goods, people and services. This complexity has resulted in an increased potential for cascading failures, whereby small scale initial failures in one system can result in events of catastrophic proportions across the wider network. Resilience and the emerging concept of resilience engineering within infrastructure are among the main concerns of those managing such complex systems. However, the disparate nature of resilience engineering development in various academic and industrial regimes has resulted in a diversity of definitions and characterisations. These are discussed in this paper, as are the commonalities between sectors and between different engineering disciplines. The paper also highlights the various methodologies used as part of resilience engineering implementation and monitoring, current practices including existing approaches and metrics, and an insight into the opportunities and potential barriers associated with these methodologies and practices. This research was undertaken for the Resilience Shift initiative to shift the approach to resilience in practice for critical infrastructure sectors. The programme aims to help practitioners involved in critical infrastructure to make decisions differently, contributing to a safer and better world.}, | ||
| language = {en}, | ||
| number = {3}, | ||
| urldate = {2021-01-06}, | ||
| journal = {Environment Systems and Decisions}, | ||
| author = {Hickford, Adrian J. and Blainey, Simon P. and Ortega Hortelano, Alejandro and Pant, Raghav}, | ||
| month = sep, | ||
| year = {2018}, | ||
| pages = {278--291}, | ||
| file = {Springer Full Text PDF:C\:\\Users\\edwar\\Zotero\\storage\\Q5AH9GR5\\Hickford et al. - 2018 - Resilience engineering theory and practice in int.pdf:application/pdf} | ||
| } |
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