Assessment of Critical Infrastructure System Interdependencies

1
Assessment of Critical Infrastructure System
Interdependencies
PHD Dissertation Proposal
Committee MembersH. Scott Matthews (CEE
EPP)Chris Hendrickson (CEE)James H. Garrett
(CEE)Paul Fischbeck (SDS EPP)

• Presenter Ping Chen
• Department of Civil and Environmental Engineering
• Carnegie Mellon University

2
Motivation

• Infrastructure sectors identified by the U.S
  Presidents Commission on Critical Infrastructure
  Protection (PCCIP)
• information and communications, physical
  distribution, energy, banking and finance, and
  vital human services
• Infrastructure Interdependence Facts
• 1999 June, WA, SCADA system failure, Pipeline
  system shutdown for one year
• 2001 Early, CA, electricity outage
• 2001 July 19, Baltimore Tunnel Train Derailment
  and Fire
• 2001 Sep 11, NY WTO Terrorist Attack
• Pros and Cons of Rapidly Growing Interdependence
• Enable these infrastructure sectors to provide
  more advanced, efficient and convenient service
  for use
• Threats on these sectors have come from multiple
  facets inside or outside natural or manmade,
  etc.
• Infrastructures now become more vulnerability
  than before because of interdependence induced
  threat
• Further efficiencies might be difficult to
  realize because of tradeoffs with induced
  vulnerabilities Heller 2002

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Research Questions

• Given the current status of knowledge about
  infrastructure interdependence which is confined
  to the realm of qualitative analysis, what would
  be an effective and feasible measurement that can
  quantitatively represent their interdependencies?
  
• What kind of model is desired that is able to
  measure the interdependency using the measurement
  defined above and how to build it?
• How does one validate whether the proposed model
  is effective for representing the interdependency
  effect and what are the uncertainties in this
  model?
• How would the derived model inform us about the
  vulnerability of individual infrastructure sector?

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Overview of Approach and Defined Tasks

• Task 1 Review Current Knowledge on
  Infrastructure Interdependence and Propose
  Quantitative Measurement Strategy
• Task 2 Review and Evaluate Interdependence
  Modeling Method
• Task 3 Develop Resilient Supply Driven
  Infrastructure Interdependence Modeling Method
• Task 4 Apply and Interpret Revised
  Infrastructure Interdependence Model
• Task 5 Analyze Model Uncertainty and Verify
  Model Soundness
• Task 6 Assess Interdependence Induced Critical
  Infrastructure Vulnerability

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Task 1 Current State of Knowledge on
Infrastructure Interdependence
Examples of Infrastructure Interdependence
Dimensions for Describing Infrastructure
Interdependence
Source Rinaldi et al, Identifying,
Understanding, and Analyzing Critical
Infrastructure Interdependence
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Proposed Interdependence Measurement Strategy

• Consequence Measurement vs. Dimensional
  Measurement
• Indicators (1) economic loss (2) inoperability
• Physical connection is the major interdependence
  type
• Two dependence-related disruption type with
  examples

Type I Demand-driven
Type II Supply-driven
Interconnected Infrastructure Sector
Initially Affected Sectors
The initially affected sectors
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Task 2 Review and Evaluation of Relevant
Modeling Methods
Industry-to-Industry Transaction Data in Detail
Output identity
Final Demand
Fixed Input Coefficients

• Leontief IO Model

• Ghosh IO Model

Primary Input
Fixed Output Coefficients
Input identity
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• Leontief IO Model
• c (0, 0, ,0, 1, 0,0)
• output
• Application
• Energy Consumption Estimation
• Environmental Implication (www.eiolca.net)

• Ghosh IO Model
• v (0, 0, ,0, 1, 0,0)
• output
• Application
• International Comparisons, Forward Linkages, and
  Key Sectors
• Sectoral Impact Studies

Final Demand Power Generation and Supply
(million)
Primary Input Power Generation and Supply
(million)
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Current Status of Extending EIO Model to
Demand-Driven Infrastructure Interdependence
Modeling
Haimes and Jiang 2001 Haimes, Y. Y., Jiang,
P. Leontief-based model of risk in complex
interconnected infrastructures, (2001)

• c - the demand-side perturbation vector
  expressed in terms of normalized degraded final
  demand
• A - the interdependency matrix that indicates
  the degree of coupling of the industry sectors
  whose elements in a particular row of this matrix
  can tell how much additional inoperability is
  contributed by a column industry to the row
  industry.
• q - the accumulated inoperability vector
  expressed in terms of normalized economic loss.

Telecommunication
Transportation
Power
Water
Power
Supposed Interruption in the transportation
sector by 10
Transportation
Example
Water
Telecommunication
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Extending Ghosh Model to Supply-Driven
Interdependence Model?

• Feasibility?

• Difficulty and Limitation?
• Less applications of supply-driven model than
  demand-driven model
• Tracing forward impact is harder than backward
  impact substitution, backup ability, etc
• Reduced demand terminates supply immediately.
  However, supply may affect consumption sector
  only gradually and it may get recovered with
  pre-planned risk mitigation actions
• More Restraints
• Bottleneck effect
• Various effects from different levels
  Interdependence
• Time effect the speed that supply constraints
  take effect depends on multiple factors
• Ghosh model returns the worst situation of supply
  constraint

Example Perturbation Sector Power Generation
and Supply Perturbation Scale Inoperability
10
Ghosh Model Reexamination Power Generation
Perturbation
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Survey Sample (from Water Sector Infrastructure
Dependency Survey)

• Question 4 Assume that you have your normal
  operation at your water supply plant, but that
  the input from one of these infrastructure
  sectors is completely cut off, due to a strike,
  accident or other disruptions. What is your
  estimation of the longest time that your normal
  water supply could continue based only on your
  normal inventory or back up (e.g. by using your
  own electric generation capacity) with a
  disruption from one of the following
  infrastructure sectors?

4
3
2
1
Point
5
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Interdependence Evaluation from Practitioners
Responded Impact Assessment vs. Direct Requirement
Responded Impact Assessment vs. Direct Supply
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Summary from Evaluations of Existing
Interdependence Model

• EIO model, both Leontief and Ghosh model provide
  good bases for extending to infrastructure
  interdependence model
• Meanwhile, both models are criticized for the
  assumption of fixed coefficients, supply
  constrained model is constrained more than the
  demand driven model because of bottleneck effect
• The distribution of the survey data is quite
  close to the output of the supply-driven model
  rather than the demand-driven model, which means
  that it best supports the supply-constraint
  impact estimation problem
• To measure the all-around impact that is
  proposed, the survey data provides a good
  information source about the sectors empirical
  ability on offsetting the negative effect of
  supply unavailability
• The survey data supplements the economic input
  output data for forming a more resilient supply
  driven infrastructure interdependence model
• Supply-driven model is better called
  supply-constrained model
• Bottleneck sector without it, the production
  ceases at no time

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Task 3 Develop Resilient Supply-Constrained
Infrastructure Interdependence Modeling Method

• Phase I Establish Industry-to-Industry Direct
  Supply Matrix
• Phase II Formulate Supply Constrained (SC)
  Economic Interdependence Matrix Improved by
  Empirical Evaluation
• Phase III Derive Supply Constrained Impact
  Estimation Model

A Direct Requirement Matrix the vector of
output from sector i
B Direct Supply Matrix S Empirical
Interdependence Matrix
(1) Economic Loss Impact
(2) Inoperability Impact
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Phase II Revised Supply Driven Interdependence
Model

• Method 1 Simple Weight Updated Coefficients
• Method 2 Bayesian Method Updated Coefficients
• Method 3 Empirical Knowledge Based Inoperability
  Estimation Model

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Preliminary Result and Analysis (Simple Weight
Method)
1. Direct Supply Matrix
2. Survey Response
Dependence Multiplier (Direct Supply vs. Adjusted
Direct Supply)
Survey Response Normalization
3. Simple Weight Updated Coefficients ( )
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Task 4 Interdependence Model Application and
Interpretation

• Scenario 1 General Inter-infrastructure Impact
• Estimate the chain disruptions among
  infrastructure sectors and non-infrastructure
  sectors for hypothetically generated
  perturbations.
• Scenario 2 Energy Security Concern
• Estimate the influence on the entire economic
  sectors as the result of reduced amount of
  imported gasoline
• Relevant energy security cases need to be further
  collected and adapted to fit the data requirement
  of the proposed mode
• Scenario 3 Transportation Access Connectivity
• Apply the decomposed EIO data on regional
  supply-driven interruption inoperability
  estimation mode
• Validate the impact from curtailed transportation
  accesses caused by unexpected events such as
  labor strike
• Potential data source
• Transportation Satellite Account (TSA)
• Regional I-O Multiplier System (RIMS II)

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Task 5 Interdependence Model Uncertainty
Analysis and Validation

• Interdependence Model Uncertainty
• Survey uncertainty
• EIO-LCA Uncertainty Analysis
• Old data
• Incomplete data
• Missing data
• Aggregation
• Imports
• Validation Case Requirement
• Dynamic Continuous Report Economic Loss Data
• EIO-LCA Validation Experience
• Relative Comparison would be more reliable and
  representative

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Task 6 Interdependence Induced Critical
Infrastructure Vulnerability Assessment

• Dependence induced vulnerability comes from both
  demand-driven disruption and supply-constraint
  disruptions threats
• Different order independence offer different
  effect on vulnerability
• Two factors that affect vulnerability
• The probability of occurrence of various threat
  scenarios originating from different sectors
• The consequence of the implementation of each
  threat scenario on the sector of interest
• Proposed vulnerability measurement

R The vulnerability assessed on one
infrastructure sector Pi The probability for
the occurrence of threat from source i Ci The
consequence of the occurrence of threat from
source i n The number of threat sources
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Expected Contribution

• Feasible and effective quantitative measurement
  of infrastructure interdependence has been
  proposed that avoids the complex and perplexing
  work of enumeration and quantification of each
  interdependency dimension
• Various interruption occurrences have been
  categorized into two groups demand-driven or
  supply-driven interruptions
• Develop Empirical Supply-Driven Infrastructure
  Interdependence Model (EMSD-IIM) than can assess
  the interdependence of the impact that the loss
  of infrastructure sectors service can bring to
  other sectors directly or indirectly
• The empirical evaluation of interdependences has
  been, for the first time, incorporated to count
  the risk-mitigation capacity of these sectors in
  reality to evaluate interdependence effect
• The interdependence induced vulnerability of
  these infrastructure sectors has been proposed to
  be measured that considers the occurrence and
  combination of these two interruption types in
  addition, the contribution to the overall
  vulnerability from various levels
  interdependence has been adjusted

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To-Do Tasks and TimeLine
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• Thanks!
• Questions, Comments ??