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SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies
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SMART International Symposium for Next Generation Infrastructure:Identifying Extreme Risks in Critical Infrastructure Interdependencies

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A presentation conducted by A/Prof Kang Tai …

A presentation conducted by A/Prof Kang Tai
Nanyang Technological University.
Presented on Thursday the 3rd of October 2013.

Critical infrastructures like our power generation facilities and water supply form highly interconnected networks that are mutually dependent and any failure can cascade through the network, resulting in devastating impact on health, safety and the economy. These catastrophic events/disruptions can be triggered by environmental accidents, geological/weather phenomena, disease pandemics, etc. The disruptions can be caused/exacerbated by their being unexpected, but they may actually be expected if relevant data have been accounted for. To help account for and thereby anticipate
such disruptions, one way is to identify potential unforeseen interdependencies among infrastructure components that can lead to extreme disruptions upon some failure in the network. This paper shows how a simulation model for cascading failures and a risk analysis/optimization approach can be applied to search for unforeseen interdependencies and failure points that give rise to the highest risk in a network.

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  • 1. ENDORSING PARTNERS Identifying Extreme Risks in Critical Infrastructure Interdependencies The following are confirmed contributors to the business and policy dialogue in Sydney: • Rick Sawers (National Australia Bank) • Nick Greiner (Chairman (Infrastructure NSW) Monday, 30th September 2013: Business & policy Dialogue 3rd www.isngi.org Tuesday 1 October to Thursday, October: Academic and Policy Dialogue Presented by: A/Prof Kang Tai, Nanyang Technological University www.isngi.org
  • 2. Identifying Extreme Risks in Critical Infrastructure Interdependencies K. Tai School of Mechanical and Aerospace Engineering, NTU A. Kizhakkedath School of Mechanical and Aerospace Engineering, NTU J. Lin School of Mechanical and Aerospace Engineering, NTU R.L.K. Tiong Institute of Catastrophe Risk Management & School of Civil and Environmental Engineering, NTU M.S. Sim Information Division, DSO National Laboratories, Singapore International Symposium for Next Generation Infrastructure SMART Infrastructure Facility, University of Wollongong Wollongong, Australia, 1 – 4 October 2013
  • 3. Critical Infrastructure • Critical infrastructure refers to the assets, systems and networks comprising identifiable industries, institutions and distribution capabilities that provide a reliable flow of goods and services essential to the functioning of the economy, the government at various levels, and society as a whole (Clinton 1996). Clinton, W.J. (1996) “Executive order 13010 - Critical infrastructure protection”, Federal Register, Vol.61, No.138, pp.37347-37350 Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 2
  • 4. Critical Infrastructure for a Modern Society/Economy Agriculture and Food Drinking Water and Treatment Plants Health Care and Civil Defence Banking and Finance Energy Transportation Systems Communication and Information Technology Military Installations and Defence Commercial and Industry Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 3
  • 5. Critical Infrastructures form Interconnected Networks with Complex Interdependencies Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 4
  • 6. Classification of Infrastructure Interdependencies • Physical – A physical or engineering reliance between infrastructures, e.g. material flow from one infrastructure to another • Information / Cyber – An informational or control requirement between infrastructures, e.g. a reliance on information transfer between infrastructures • Geospatial / Geographic – A relationship that exists entirely because of the proximity of infrastructures, e.g. a local environmental event affects components across multiple infrastructures due to physical proximity • Policy / Procedural – An interdependency that exists due to policy or procedure that relates a state or event change in one infrastructure sector to a subsequent effect on another sector, e.g. government’s emergency mandatory orders on a particular area due to the influence of an event • Societal / Logical – An interdependency that an infrastructure event may have on societal factors, e.g. public opinion, public confidence, fear, and culture issues (Rinaldi et al. 2001, Pederson et al. 2006) Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 5
  • 7. Complex Interdependencies Lead to Infrastructure Disruptions with Widespread Consequences 9/11 terrorist attacks 2011 Tohoku earthquake/tsunami 2008 global financial crisis 2011 floods in Thailand Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 6
  • 8. Unforeseen Interdependencies Banking and Financial Infrastructures 9/11 terrorist attacks Transportation Infrastructures Military Infrastructures Global Impact Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 7
  • 9. Black Swans • The idea that such high impact but highly unexpected events could actually have been expected if the relevant available data had been accounted for was put forth by Taleb in his book “The Black Swan”. • Black Swan events are highly improbable events (outliers), and highly impactful, and can be caused and/or exacerbated by their being unexpected (Taleb 2007). • However, in spite of being highly unexpected, it is natural that experts (and even casual observers) will retrospectively be able to construct explanations for their occurrences after they have occurred, making them explainable and expected. Taleb, N.N. (2007) The Black Swan: The Impact of the Highly Improbable, Random House Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 8
  • 10. Analyzing Vulnerabilities in Critical Infrastructure Networks by Network Modelling/Analysis sector 1 sector 2 sector 3 interdependency (known) interdependency (unforeseen) Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 9
  • 11. Multiobjective Optimization of Risk • Risk Analysis Framework – risk = f (probability, impact) • Multiobjective Optimization Problem – searching for maximum probability of occurrence of failure/hazard/threat – searching for maximum impact of disruption (minimum giant component size) • Decision Variables – unforeseen interdependencies – failure point(s) Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 10
  • 12. Decision Variables in Multiobjective Optimization Problem Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 11
  • 13. Multiobjective Optimization by Genetic Algorithms (GA) begin initialize population of networks selection and recombination/mutation to populate next generation compute failure probabilities & compute disruption termination/ convergence criteria no yes stop Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 12
  • 14. kS wa n Pareto front Bl ac probability Anticipating Extreme Risks by Multiobjective Optimization wan S ack Bl disruption/impact Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 13
  • 15. Experimental Test Problem Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 14
  • 16. Experimental Test Problem – Agent-Based Modelling/Simulation Using NetLogo Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 15
  • 17. Experimental Results – Single Objective Opt. (Maximize Impact with Single Node Failure/Attack) Node failed No. of unforeseen Unforeseen interdependencies added interdependencies added Giant component size 28 0 Nil 36 28 1 One of (7→3, 8→3, 11→3, 15→3, 17→3, 28→3, 31→3) 32 28 2 One of (7→3, 8→3, 11→3, 15→3, 17→3, 28→3, 31→3) and one of (3→19, 4→19, 13→19, 15→19, 21→19, 28→19) 30 Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 16
  • 18. Experimental Results – Single Objective Opt. (Maximize Impact with Single Node Failure/Attack) Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 17
  • 19. Experimental Results – Multiobj. Opt. (2 Unforeseen Interdepend. & Single Node Failure/Attack) Node Probability Giant failed comp. size 28 0.1 30 9 0.26 33 15 0.36 34 31 0.41 35 1, 5, 12, 43 0.5 36 Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 18
  • 20. Experimental Results – Multiobj. Opt. (2 Unforeseen Interdepend. & Single Node Failure/Attack) Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 19
  • 21. Experimental Results – Multiobj. Opt. (2 Unforeseen Interdepend. & Double Node Failure/Attack) Nodes failed Probability 28, 41 0.0080 Giant comp. size 19 28, 36 0.0130 21 28, 14 0.0200 22 28, 16 0.0320 27 28, 1 0.0500 28 9, 15 0.0936 30 27, 15 0.1152 31 27, 43 0.1600 32 (1,15),(5,15), (12,15),(43,15) (1,31),(5,31), (12,31),(43,31) (12,43),(1,12), (1,5),(1,43), (5,43),(5,12) 0.1800 33 0.2050 34 0.2500 35 Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 20
  • 22. Experimental Results – Multiobj. Opt. (2 Unforeseen Interdepend. & Double Node Failure/Attack) Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 21
  • 23. Concluding Remarks • The experiments show that unforeseen interdependencies can indeed exacerbate the disruption consequences/impact, with the extreme disruptions interpreted as Black Swan events. • The methodology can serve as a tool for scenario planning, by helping policymakers to anticipate and thereby focus on the “worst case” scenarios. • The multiobjective optimization approach also provides a way for policymakers to analyze the “trade-off” between the highprobability/low-impact events and the low-probability/high-impact events. Tai et al. – Identifying Extreme Risks in Critical Infrastructure Interdependencies (ISNGI 2013) 22
  • 24. Contact : Associate Professor K. Tai School of Mechanical and Aerospace Engineering, Nanyang Technological University Phone : 67904444 Email : mktai@ntu.edu.sg URL : http://www.ntu.edu.sg/home/mktai/

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