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Seminar at University of Oxford | 20160120 | Jonas Johansson

Critical Infrastructures – Interdependencies and consequences from a vulnerability perspective

LUND UNIVERSITY | FACULTY OF ENGINEERING | CENCIP & LUCRAM | SWEDEN DIVISION OF RISK MANAGEMENT AND SOCIETAL SAFETY

JONAS JOHANSSON


Critical Infrastructures (CIs)? • “…those assets or parts thereof which are essential for the maintenance of

critical societal functions, including the supply chain, health, safety, security, economic or social well-being of people” (EPCIP – COM, 2006)

• Brief history – From sector regulations towards holistic infrastructure protection – Starting point for the field; Executive Order 13010 (Executive Order, 1996), creating

PCCIP in the USA.

– 9/11 in 2001 and Hurricane Katrina in 2005 illuminated the importance and vulnerability of critical infrastructure. Creation of DHS and intensified work. From terrorism towards all-hazard approaches.

– In Europe, the EPCIP program was initiated in 2006.

– Today most countries around the world have programs focused towards CIP, i.e. moving from earlier “sector-divided” approaches towards more holistic infrastructure protection approaches.

– A response to the interconnectedness of todays infrastructures – the backbone of society!


Rationale

• Society heavily dependent on the services of critical infrastructures, widespread disruption entails large-scale societal impacts.

• Hence:

– Proactive risk and vulnerability approaches and long term planning fundamental

– Of essence is to increase our understanding CIs limits, their interdependencies and societal dependence on the services these provide

• However, there exist several research, policy, and practical challenges for a holistic understanding and a fundamental need for development of approaches and methods in this field.

Hurricane Gudrun, Sweden 2005

Ice storm, Canada 1998

Blackout, USA 2003

Auckland 1998


Six challenges and examples of research at LU

I. Addressing high impact and low probability events

II. Empirical data for cascading effects in critical infrastructures

III. Modelling and simulation of interdependent technical critical infrastructures

IV. Recovery and resilience of technical critical infrastructures

V. Interdependencies between societal functions and dependence on technical infrastructures

VI. Risk governance of critical infrastructures


Challenge 1 Addressing high impact and low probability events

• Due to the complexities of national critical infrastructures; the services they provide, the operation of them, and the environment in which they operate To address HILP use vulnerability as a complement to risk (?)

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Challenge 1 Addressing high impact and low probability events

Vulnerability seen as a property of to the system states

and the consequences associated with these states

Risk = f(Hazard/Threat, Susceptability, System State, Consequence)

Models: E.g. Power flow AC/DC

Pressure models Traffic flow models Cascading models Stability models

Input-output models

Models: E.g. Fragility curves

Models: E.g. Aging models,

Climate models, Terrorism models…

Likelihood of an Hazard/Threat affecting the

system

Likelihood of an Hazard/Threat

occurring

Likelihood that an event/scenario affect the system, i.e. forcing it into a specific state

The consequences associated with a specific state of the system


Initiating event

1. Power supply

13. Agriculture

19. Public

2. Telecommunication

3. Water supply

5. Oil and gas

7. Health care

8. Education

9. Road transportation

10. Rail transportation

13. Agriculture

14. Business & Industry

15. Media

16. Financial

19. Public

13. Agriculture

14. Business & Industry

17. Governmental

18. Emergency response

19. Public 19. Public

Challenge 2 Empirical data for cascading effects between critical infrastructures

• To support the research in the field of critical infrastructures, one important aspect is the access to empirical data.

• In general, good quality data with respect to the cascading effects that arise when infrastructure collapses are lacking. For example traditional accident investigation methods do not focus on interdependencies.

• This type of data is essential to increase our understanding of society’s dependence, how this picture has changed and the mechanisms behind interdependencies leading to cascading effects.



Event Location Year IE type Total # Systems

Casc. order

Event duration

1 Auckland New Zealand 1998 Power outage 11 5 2m5d 2 Tieto Sweden 2011 IT-event 7 4 2m 3 UK floods UK 2007 Flooding 13 3 6m3d 4 Enschede Netherlands 2000 Explosion 6 3 3y7m 5 London bombing UK 2005 Terrorism 8 3 1y11m 6 Mont Blanc Switz. France 1999 Fire 4 2 3y3m 7 Sandy N. America 2012 Hurricane 18 5 2m1w 8 Eyjafjallagokull Island 2010 Volcano eruption 5 2 1m1w 9 Malmo floods Sweden 2014 Flooding 12 3 1d12h 10 Myyrmanni Finland 2002 Terrorism 4 3 2w4d 11 Kista blackout Sweden 2001 Power outage 9 3 1d16h 12 Östersund Sweden 2010 Contam. water 7 3 5m4w 13 Baltimore USA 2001 Tunnel Fire 10 4 2w2d 14 L'Aquila Italy 2009 Earthquake 11 2 5y

15 European blackout Europe 2006 Power outage 4 2 2h

16 Ice storm N. America 1998 Ice storm 15 4 1m1d …40



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Challenge 3 Modelling and simulation of interdependent critical infrastructures

• Technical infrastructures, such as power systems, railways, air transportation and telecommunication, form a subpart of critical infrastructures.

• Here data of individual systems exist to some extent, however data of their interdependencies and models of accounting for the “system-of-system” behaviour of interdependent technical infrastructures lacking.

• From a Swedish governance perspective adequate mechanisms for managing risk and vulnerabilities from “system-of-system” perspective lacking.

• Efforts needed to develop models and simulation methods to inform decisions from a more holistic perspective.



Computational effort vs fidelity: 1. Topological properties 2. Search algorithms 3. Flow Models 4. Dynamic simulation

Singel system representation ”System-of-system” representation


Challenge 3 Modelling and simulation of interdependent CIs

Functional model Performance/consequence measures1 Label Topological static – components are not differentiated

Largest connected subgraph (Holme and Kim, 2002) LCSG Diameter (Newman, 2003) D Average efficiency (average inverse geodesic length) (Newman, 2003; Crucitti et al, 2004) E

Topological static – components are differentiated

Average efficiency only considering pairs of in-feed and load nodes EN Average efficiency only considering pairs of in-feed and load nodes and electrical distance ENE Connectivity loss (Albert et al., 2004) CL Power connection loss (Johansson et al., 2007) PCL

Simplistic capacity model Power not supplied (Jonsson et al., 2008) PNS

Physical flow models DC load flow – power not supplied DC AC load flow – power not supplied AC

Ran

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TS96



• Full scale models of Swedish

– Transmission (DC load flow)

– Railway (tracks & trains)

– Their interdependencies (geographical and functional)

• Vulnerability analyses from three perspectives:

– Global vulnerability (stress beyond “normal”)

– Critical components (important assets to protect)

– Geographical vulnerability (co-locations, hotspots)


Challenge 4 Recovery and resilience of critical infrastructures

• Technical infrastructures are inherently socio-technical by nature - they are designed, operated, maintained and restored by humans.

• In general, research in this field tends to focus rather narrowly on “everyday” incidents (based on historical data) and technical aspects.

• To better grasp the resilience of infrastructures more work is necessary of their limits towards large-scale disruptions, e.g. their ability to recover functionality.

• Approaches needs to merge the pure technical parts of the infrastructures with models able to capture the capacity of the organisation in responding to disruptions beyond normal.


Challenge 4 Recovery and resilience of critical infrastructures

Electric distribution system

Restoration system +


El

Fjärrvärme

Bränsle och drivmedel

Betalningssystem

Tillgång kontanter

Värdepappershandel

Forsäkringar

Tillverkningsindustri

Akutsjukvård

Primärvård

Läkemedel- & Materialforsorjning

Omsorg om barn

Funktionshindrade

Äldrevård

Socialtjänst

Smittskydd

Telefoni (fast)

Telefoni (mobil)

Elektronisk kommunikation

Internet

Radiokommunikation Satellit / GNSS

Dagstidningar

Webbaserad information

MedierTV

Radio

Dricksvattenforsorjning

Avloppshantering

Renhållning

Väghållning

Distribution livsmedel

Primärproduktion livsmedel

Tillverkning livsmedel

Kontroll av livsmedel

Lokal ledning

Regional ledning

Nationell ledning

Polis

Räddningstjänst

Alarmeringstjänst (t.ex. SOS)

Tullkontroll

Bevaknings & säkerhet

Militärt forsvar

Sjuk- & arbetsloshetsforsäkring

Flygtransport

Järnvägstransport

Sjotransport

Vägtransport

Kollektivtrafik

Kompetent personal/entreprenorer

Forskolor och skolor

Sjo

Liv och hälsa

Funktionalitet

Grundläggande värden

Samhällsviktig verksamhet

Teknisk infrastruktur

Allmänheten

Personal

Challenge 5 Capturing interdependencies between societal functions

• Dependencies between societal functions seems to be increasing

• The overall “societal system” more tightly interconnected

• Trends such as globalisation, urbanisation, and technological development drivers for efficiency but also introduces new vulnerabilities and changes the risk picture.

• The understanding of the interconnectedness of these functions and the mechanisms of how consequences can spread limited. Need for new approaches and empirical data.



• Question? – How does the vulnerability of the Swedish

transmission system correlate to regional societal consequence of power outages?

• Power system – Representative DC-model of the Swedish

Transmission system – Configuration in accordance with 23rd of

September blackout in 2003

• Societal consequences – Economical Inoperability Input-Output model

(IIM) – a linear model with its deficiencies – National economical data of 55 sectors

make/use dependencies – Broken down to 21 regions (län) – Skåne, V.Gotaland, Stockholm: 57% of GRP



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0 5 10 15 20 25 30

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Vulnerability reduction (%)

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Vulnerability reduction (%)0 5 10 15 20 25 30

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Dark grey = Power supply improvement Light grey = Economical improvement


Challenge 6 Risk governance of critical infrastructures

• The operation and management of many critical infrastructures has become divided between a larger set of stakeholders, resulting in a dispersion of responsibility.

• In this institutionally fragmented setting, traditional risk management tools are not always suitable to deal with risks in a feasible manner.

• No single stakeholder has the superior authority or overview to make and implement holistic risk-reducing decisions.

• Research needs are related to stakeholders’ diverse framings of risk, communication challenges, sub-contracting and cross-scale interactions.


Centre for Critical Infrastructure Protection Research (CenCIP) • Newly formed centre of excellence at Lund University, 2015-2020.

(8 seniors, 1 Postdoc, 2 PhD-students, 20 MSEK)

• Descriptive and normative research within three areas: – Interdependencies and societal consequences

– A holistic view on terms, concepts and methods

– Governance, measuring, monitoring, and learning

www.cencip.lu.se


Please feel free to contact me

Associate Professor Jonas Johansson Division of Risk Management and Societal Safety Lund University, Faculty of Engineering

[email protected] ([email protected]) www.lucram.lu.se www.cencip.lu.se

mailto:[email protected]



http://www.lucram.lu.se/

http://www.cencip.lu.se/


International Scientific Journals (peer-reviewed) 1. LaRocca, S., Johansson, J., Hassel, H., Guikema, S., (2014). Topological Performance

Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems, Risk Analysis, doi: 10.1111/risa.12281.

2. Johansson, J., Hassel, H., Zio, E., (2013). Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems, Reliability Engineering and System Safety, Vol. 120, pp. 27-38.

3. Johansson, J., Hassel, H., Cedergren, A., (2011). Vulnerability analysis of interdependent critical infrastructures: case study of the Swedish railway system, International Journal of Critical Infrastructures, Vol. 7, No. 4, pp. 289-315.

4. Johansson, J., Hassel, H., (2010). An Approach for Modelling Interdependent Infrastructures in the Context of Vulnerability Analysis, Reliability Engineering and System Safety, Vol. 95, pp. 1335-1344.

5. Jonsson, H., Johansson, J., Johansson, H., (2008). Identifying Critical Components in Technical Infrastructure Networks, Journal of Risk and Reliability, Vol. 222, No. 2, pp. 235-243.

6. Johansson, J., Jonsson, H., Johansson, H., (2007). Analysing the Vulnerability of Electric Distribution Systems: A Step Towards Incorporating the Societal Consequences of Disruptions, Int. J. Emergency Management, Vol. 4, No. 1, pp.4–17.

International Conferences 7. Johansson, J., Hassel, H., Cedergren, A., Svegrup, L., Arvidsson, B., (2015). Method for

describing and analysing cascading effects in past events: Initial conclusions and findings, ESREL 2015, Zürich, Switzerland, September 7-10.

8. Svegrup, L., Johansson, J., (2015). Vulnerability Analyses of Interdependent Critical Infrastructures: Case study of the Swedish National Power transmission and Railway system, ESREL 2015, Zürich, Switzerland, September 7-10.

9. Arvidsson, B., Johansson, J., Hassel, H., Cedergren, A., (2015). Investigation method for cascading effects between critical infrastructures, ESREL 2015, Zürich, Switzerland, September 7-10.

10. Cedergren, A., Johansson, J., Svegrup, L, Hassel, H., (2015). Local Success, Global Failure: Challenges Facing the Recovery Operations of Critical Infrastructure Breakdowns, ESREL 2015, Zürich, Switzerland, September 7-10.

11. Hassel, H., Cedergren, A., Svegrup, L., Johansson, J., (2014). A method for identifying cascading effects in past events as an input to a decision support tool, ESREL 2014, Wroclaw, Poland, September 14-18.

12. Landegren, F., Johansson, J., Samuelsson, O., (2014). Comparing Societal Consequence: Measures of Outages in Electrical Distribution Systems, ESREL 2014, Wroclaw, Poland, September 14-18.

13. Johansson, J., Svegrup, L., Hassel, H., (2014). Contrasting vulnerability reduction measures for critical infrastructures: using power system and regional inoperability input-output models, PSAM 12, Honolulu, Hawaii, USA, June 22-27.

14. Johansson, J., Hassel, H., (2014). Impact of Functional Models in a Decision Context of Critical Infrastructure Vulnerability, ASCE ICVRAM&ISUMA 2014, Liverpool, UK, July 13-16.

15. Johansson, J., Svegrup, L., Hassel, H., (2013). Societal consequences of critical infrastructure vulnerabilities: integrating power system and regional inoperability input-output models, ESREL2013, Amsterdam, Netherlands, September 29 - October 2, 2013.

16. Landegren, F., Johansson, J., Samuelsson, O., (2013). Review of Computer Based Methods for Modeling and Simulating Critical infrastructures as Socio-Technical Systems, ESREL2013, Amsterdam, Netherlands, September 29 - October 2, 2013.

17. Johansson, J., LaRocca, S., Hassel, H., Guikema, S., (2012). Comparing Topological Performance Measures and Physical Flow Models for Vulnerability Analysis of Power Systems. PSAM11 & ESREL2012, Helsinki, Finland, June 25-29, 2012.

18. Johansson, J., Hassel, H. (2011), Comparison of vulnerability and reliability analysis of technical infrastructures. ESREL2011, Troyes, France, September 18-22, 2011.

19. Johansson, J., Hassel, H. (2011), Geographical vulnerability analysis of interdependent critical infrastructures. ICASP11, Zurich, Switzerland, August 1-4, 2011.

20. Wilhelmsson, A., Johansson, J., (2009). Assessing Response System Capabilities of Socio-Technical Systems, TIEMS2009 Istanbul, Turkey, June 9-11.

21. Johansson, J., Jonsson, J., (2008). A Model for Vulnerability Analysis of Interdependent Infrastructure Networks, ESREL2008 & SRA 17th, Valencia, Spain, September 22-25.

22. Jonsson, H., Johansson, J., Johansson, H., (2007). Identifying Critical Components in Electric Power Systems: A Network Analytic Approach, ESREL2007, Stavanger, Norway, June 25-27.

23. Johansson, J., Lindahl, S., Samuelsson, O., Ottosson, H., (2006). The Storm Gudrun a Seven-Weeks Power Outage in Sweden, CRIS2006, Alexandria, VA, USA, September 25-27.

24. Johansson, J., Jonsson, J., Johansson, H., (2006). Analysing Societal Vulnerability to Perturbations in Electrical Distribution Systems. CNIP06, Rome, Italy, March 28-29.

25. Johansson, J., (2014). Discussion of a framework for interdependent critical infrastructure vulnerability analysis from a climate change perspective, Deltas in time of climate change II, Rotterdam, Netherlands, September 24-26.

26. Johansson, J., Kjølle, G., Gjerde, O., (2014). Methods for Vulnerability Analysis of Power Systems, NORDAC 2014, Stockholm, Sweden, September 8-9.

27. Hassel, H., Johansson, J., (2013). Developing a new method for mapping societal functions, flows and their dependencies – results from an initial study. SRA Annual Meeting, Baltimore, USA, December 8-11.

28. LaRocca, S., Johansson, J., Hassel, H., Guikema, S., (2012). Topological performance measures as surrogates for physical flow models for electric power systems. SRA Annual Meeting, San Francisco, USA, December 9-12.

29. Johansson, J., Svensson, S., (2008). Risk and Vulnerability Management of Electrical Distribution Grids, NORDAC 2008, Bergen, Norway, September 8-9.

30. Johansson, J., Willhelmsson, A., (2008), Vulnerability Analysis of Socio-Technical Systems: Addressing Railway System Vulnerabilities, Young Researches Seminar, Malmo, Sweden.

Monographs 31. Johansson, J., (2010). Risk and Vulnerability Analysis of Interdependent Technical

Infrastructures, Doctoral Thesis, Department of Measurement Technology and Industrial Electrical Engineering, Lund University, Lund.

32. Johansson, J., (2007). Risk and Vulnerability Analysis of Large-Scale Technical Infrastructures, Licentiate Thesis, Department of Industrial Electrical Engineering and Automation, Lund University, Lund.

Books and Book Chapters 33. Utne, I.B., Hassel, H., Johansson, J., (2012). A Brief Overview of Some Methods and

Approaches for Investigating Interdependencies in Critical Infrastructures. In Hokstad, P., Utne, IB., Vatn, J., (Eds), (2012). Risk and Interdependencies in Critical Infrastructures – A Guideline for Analysis (pp. 1-12). London, Springer-Verlag.

34. Johansson, J., Hassel, H., (2012). Modelling, Simulation and Vulnerability Analysis of Interdependent Technical Infrastructures. In Hokstad, P., Utne, IB., Vatn, J., (Eds), (2012). Risk and Interdependencies in Critical Infrastructures – A Guideline for Analysis (pp. 49-66). London, Springer-Verlag.

35. Johansson, J., Hassel, H., (2012). Vulnerability Analyses of Interdependent Technical Infrastructures. In Hokstad, P., Utne, IB., Vatn, J., (Eds), (2012). Risk and Interdependencies in Critical Infrastructures – A Guideline for Analysis (pp. 67-94). London, Springer-Verlag.


Reports and other publications 36. Johansson, J., Hassel, H., Cedergren, A., Svegrup, L., Arvidsson, B. (2015). Review of

previous incidents with cascading effects, Deliverable 2.2 in EU-project CascEff. 37. Cedergren, A., Johansson, J., Svegrup, L. and Hassel, H. (2015). Kritiska Funktionsområden:

Resultat från fas 2 – Inventering av aktörer involverade i hanteringen av störningar i järnvägssektorn (Critical societal functions: Results from phase 2 – Analysis of actors involved in the handling of railway disturbances), LUCRAM report 3001, LUCRAM, Lund University, Lund.

38. Johansson, J., Hassel, H., Petersen, K., Arvidsson, B., (2015). Konsekvensanalys på samhällsnivå (Analysis of societal consequence), LUCRAM report 3002, ISRN: LUTVDG/TVRH--3002—SE, Lund University,Lund University, Lund, Sweden. (On behalf of the Swedish Civil Contingency Agency)

39. Johansson, J., Svegrup, L., Arvidsson, B., Jangefelt, J., Hassel, H., Cedergren, A., (2014), Method to study cascading effects, Deliverable 2.1 in EU-project CascEff.

40. Johansson, J., Svegrup, L., Kihl, M., (2014). Studie avseende komplexa beroenden mellan telekommunikationsinfrastrukturer inom sektorn Information och Kommunikation (Study of complex dependencies of telecommunication-infrastructures with the sector information and communication), LUCRAM report 3186, Lund University, Lund, Sweden. (On behalf of the Swedish Civil Contingency Agency)

41. Hassel, H., Johansson, J., Petersen, K., Svegrup, L., (2014). Kunskapsöversikt – Skydd av samhällsviktig verksamhet (Systematic review – Critical infrastructure protection), LUCRAM report 3001, Lund University, Lund, Sweden. (On behalf of the Swedish Civil Contingency Agency)

42. Johansson, .J., Svegrup, L., Hassel, H. (2013). Studie och översiktlig utvärdering kring applicerbara metoder för komplex beroendeanalys på såväl sektoriell som tvärsektoriell nivå (Analysis and overview of applicable methods for complex interdependency analysis at sectorial and cross-sectorial level), LUCRAM report 3177, Lund University, Lund, Sweden. (On behalf of the Swedish Civil Contingency Agency)

43. Johansson, J., Samuelsson, O., Hassel, H., (2010). Tekniska infrastrukturers sårbarhet (Technical infrastructures vulnerability). Chapter in FRIVA – Risk, Sårbarhet, och Formåga - Samverkan inom krishantering, Final report for research project FRIVA2, Lund University, Lund, Sweden.

44. Johansson, J., Jonsson, H., Johansson, H., (2008). Sårbarhetsanalys av tekniska infrastrukturer, (Vulnerability analysis of technical infrastructures) in Risk- och sårbarhetsanalys: Utgångspunkter for praktiskt arbete, FRIVA, Lund University, Lund, Sweden.

45. Johansson, H., Jonsson, H., Johansson, J., (2007). Analys av sårbarhet med hjälp av nätverksmodeller (Analysis of vulnerability with network theoretical modelling), LUCRAM report 1011, Lund University Lund, Sweden.

46. Petersen, K., Johansson, H., Jonsson, H., Johansson, J., (2007). Utlåtande rorande Riksrevisionens dokument ”Aktivitet 7A: Bedöming av helhetsbild avseende risk- och sårbarhetsanalyser” och ”Aktivitet 7B: Risker och sårbarheter som kan vara bristfälligt analyserade/hanterade”, Reports to the Swedish National Audit Office, Department of Fire Safety and Engineering, Lund University, Lund, Sweden.

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