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CREATE OVERVIEW
Detlof von WinterfeldtProfessor of Industrial and Systems Engineering
Professor of Public Policy and Management
Center for Risk and Economic Analysis of Terrorism Events
University of Southern California
Fall, 2008
Why Risk Analysis?
“….We have to identify and prioritize risks -- understanding the threat, the vulnerability and the consequence. And then we have to apply our resources in a cost-effective manner….. “
Why Economic Analysis?
“If their economy is destroyed, they will be busy with their own affairs rather than enslaving the weak peoples. It is very important to concentrate on hitting the US economy through all possible means.”
CREATE is an Interdisciplinary Center
• Social Science– Economics
– Psychology
– Political Science
• Engineering– Industrial and Systems Engineering (OR)
– Civil Engineering
– Computer Science
• Other– Public Policy
– Decision Science
– International Relations
CREATE Researchers• 40 faculty members
– 40 tenure track faculty members– 10 adjunct, research professors, etc.
• 20 Other Researchers– 6 Postdoctoral Research Associates– 14 research scientists, computer scientists, etc.
• 40 Research Assistants– Mix of Ph.D. and Masters students– First batch of Ph.D. students graduated in 2007
• Quality Indicators– Ten researchers with 1,000+ citations (ISI Web of Science)– One member of the NAS, two members of the NAE– Two presidents, four fellows of INFORMS
CREATE Models
• Risk Assessment– Probabilistic Risk Analysis– Game Theory– Terrorist Utility Models
• Economic Assessment– Advanced Economic Impact Models (I/O and CGE)– Economic Analyses of Terrorist Behavior – Models of Public Responses and Resilience
• Risk Management– Dynamic, Adaptive Decision Analysis– Game theoretic models for inspections and patrols– Optimal Resource Allocation Models
Examples of Center Projects and Products
Applied Research ProjectsAnalysis of dirty bomb attacks on portsAllocation of funds to critical infrastructureEconomic analysis of bioterrorism eventsRandomization of inspections and patrols
Fundamental Research ProjectsGame theory extensions to terrorism problemsDecision analysis with adaptive responsesProbabilistic models of terrorist preferencesNetwork reliability and failure models
Software DevelopmentRisk Analysis Workbench (RAW)MANPADS Decision Tree SoftwareNational Interstate Economic Impact ModelRandomization software
CREATE Research Framework
Threat Assessment
ConsequenceAssessment
VulnerabilityAssessment
Risk Assessment
CREATE Research Framework
Threat Assessment
ConsequenceAssessment
VulnerabilityAssessment
Valuation ofDirect Econ.
Consequences
Estimation ofIndirect Econ.Consequences
Risk Assessment
Eco
nom
ic A
ssessm
en
t
Assessment ofResilient
Responses
Overall Framework
Threat Assessment
ConsequenceAssessment
VulnerabilityAssessment
Assessment ofIndirect Econ.Consequences
ResponseRecovery
Prevention Protection
Cost-Benefit & Decision Analysis
Risk AssessmentEconomic
Assessment
Risk Management
Valuation Of Direct
Consequences
Risk Analysis: Over 30 Years of Experience
• Reliability engineering (aerospace industry)• Nuclear power plant risks• Chemical and other industrial risks• Environmental risks• Natural disaster risks• Business, project and R&D risks• Medical risks
Attempts to Apply Risk Analysis to Terrorism
– Probabilistic risk analysis– Dynamic adaptive decision tree analysis– Game theory– Vulnerability and risk scoring systems____________________________________
Hardest Part: Threat Analysis
Lugar Report: Threat Probabilities
Lugar SurveyProbabilities of Major Attacks
Event
Median Probability (5 Years)
Median Probability (10 Years)
Appr. Sample
Size
Nuclear Attack 10% 20% 80Biological Attack 10% 20% 80Chemical Attack 15% 15% 80Radiological Attack 25% 40% 80
Selected Participants in the Luger Study
• Richard Allen• Graham Allison• Frank Carlucci• Bill Cohen• James Dobbins• Amitai Etzione• Bob Galluci• Sig Hecker• Ron Lehman
• Michael Moodie• Sam Nunn• Noman Schwarzkopf• Strobe Talbott• James Woolsey
+ 70 others
Assessing the Threat of Bioterrorism
Bacillus Anthracias(Anthrax): Communicable Impact Quantity: 100 kilogram fatal to 3 million persons Mortality Rate: 25% to 60%
Bacillus Anthracias(Anthrax): Communicable Impact Quantity: 100 kilogram fatal to 3 million persons Mortality Rate: 25% to 60%
Yersinia pestis
(Plague):
Communicable
Impact Quantity: 1 infected person creates 10 new cases
Mortality Rate: 15% to 60%
Raciness communis(Ricin):Non-Communicable Impact Quanity:1 milligram can kill an adultMortality Rate: 50% to 85%
Non-communicable
Expert Elicitation
• Elicitation of selection probabilities of 28 agents• Four bioterrorism experts• Two risk analysts (Hora, von Winterfeldt)• Hierarchical elicitation• Software support
Expert Elicitation- Observations
• A few biological agents float to the top for all experts (and non-experts)
• Worked well with experts who had biological knowledge
• Some problems with experts who did not have biological knowledge
• Nevertheless: High correlation between experts’ risk assessments (0.87)
Terrorists’ Utility Functions
• Develop a muliattribute utility function for terrorists’ preferences for attack modes and targets– Initial focus on Al Quaeda and selected attack modes
• Develop an expected utility function– Folding in probability of success
• Develop a random expected utility model– Using parameter uncertainty
• Derive probabilities of choice– Initially for Al Quade and choice of attack modes
Radical Islamist Fundamentalists’ Goals
Re-establish the Caliphate
Expel US fromMiddle East
Replace SecularGovernments
In Middle East
EliminateIsrael
ExpandMuslim
Influence
Attack US Attack Arab
States
Attack
Israel Recruit
Followers
The expanse of the Caliphate by 1500 included most of Africa, the middle east, much of SW Asia, and SE Europe.
The enemy is focused on the history of the Muslim world – which drives much of the extremist ideology
In A.D. 900, the Caliphate included most of present day Spain and portions of France and Italy
24
Source: Admiral Sullivan, 2006
Terrorists’ Value Tree
Increasedpower base
Maximizerecruitment
Maximize pop. support
(sympathizers)
Maximizefunding
Minimize“backlash”To Al Qaeda
Lowoperational
expenditures
Minimizecost
Minimizeresources
High impact on theUnited States
Humancausalities
Economicimpact
Instillfear
ST immediatedamage
LT rippleeffects
High Value Attack on US
Attack Alternatives Considered
ALTERNATIVES
No attack (baseline)
IED engine room of naval vessel
Explosion resulting in dam failure
MANPADS attack on airplane
Portable nuclear bomb in major city
Explosions on mass transport(s)
Release of anthrax (movie or sports)
Detonation of dirty bomb
Smallpox release in major city
Event Tree: Indicates various possible points of failure
PM
1-PM
PI
1-PI
PS
1-PS
MaterialAcquisition?
FailedAttack
Failure
Success Interdiction?
FailedAttack
FailedAttack
TriggerEvent
Success
Failure
SuccessfulAttack
Success
Failure
Attack Utility (conditional on Success)
Attack Type Utility (assuming successful attack)
No Attack 0.16
IED 0.18
Dam Explosion 0.17
Manpad 0.16
Portable Nuclear Device 0.45
Transport. Systems 0.17
Anthrax 0.26
Dirty Bomb 0.18
Smallpox 0.46
Expected Utility of Attack(including event tree uncertainties)
Attack Type Expected Utility
No Attack 0.16
IED 0.14
Dam Explosion 0.11
Manpad 0.10
Portable Nuclear Device 0.06
Transport. Systems 0.12
Anthrax 0.11
Dirty Bomb 0.08
Smallpox 0.07
Overall Framework
Threat Assessment
ConsequenceAssessment
VulnerabilityAssessment
Assessment ofIndirect Econ.Consequences
ResponseRecovery
Prevention Protection
Cost-Benefit & Decision Analysis
Risk AssessmentEconomic
Assessment
Risk Management
Valuation Of Direct
Consequences
Smart Randomization (Tambe et al)
• Terrorists monitor defenses, exploit patterns• Examples: Patrols, inspections, surveillance • Randomize defenses, maintain quality
Expected Utility of Attacker
-1
0
1
2
3
4
5
6
7
8
9
10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Probabiliy of Defender Choosing A
Att
ac
ke
r's
Ex
pe
cte
d U
tilit
y
u(A)
u(B)
Solution
• Set p(Defend A) to minimize attackers maximum expected utility
• Also maximizes defender’s minimum expected utility
• Example: p = 11/17
Extensions
• Non-zero sum• Multiple targets• Multiple attackers• Constraints on real world patrols• Fast algorithms• Real world implementation
Assistant for Randomized Monitoring Over Assistant for Randomized Monitoring Over Routes (ARMOR) ProjectRoutes (ARMOR) Project
An Interdisciplinary Counter-Terrorism Research Partnership:
Los Angeles World Airports & The University of Southern California
ARMOR SystemARMOR System
DOBSS: GAMETHEORY
ALGORITHMS
Provide inputs, constraints
RandomizedSchedule
generation
Weights forrandomization
Schedule evaluation
ARMOR Knowledge Base
The Element of SurpriseTo help combat the terrorism threat, officials at Los Angeles International Airport are introducing a bold new idea into their arsenal: random placement of security
checkpoints. Can game theory help keep us safe?
Security forces work the sidewalk at LAX
September 28, 2007
Resource Allocation to Protect Infrastructure Assets
• Develop practical decision analysis tools for allocating Department of Homeland Security funds
• First case study: BZPP Fund Allocation• Conducted with the California Governor's Office of
Homeland Security
Selected Sites in California
Chemical: High fatality potential
Commercial: high threat
Dams: Fatality & economic impact potential
“Only” Five Inputs Required per Site
1. Threat: Probability of Attack (P)
2. Vulnerability: Probability Attack Succeeds (Q)
3. Consequences: Expected Loss if Attack Succeeds (L)[$-equivalent losses]
4. Loss Reduction: Loss Reduction with RMP (0 < R < 1)
5. Cost: Cost of Risk Reduction (C)
Expected loss: No RMP: EL = P∙Q∙LWith RMP: EL´ = P∙Q∙L∙(1-R) + C
Net loss reduction: (EL - EL´) = P∙Q∙L∙R – C
Three Sectors Appeared to Be Higher RiskSector Comparisons (CREATE)
Fatality Range
Economic
Impacts
Threat and
Vulnerability
Risk
Reduction Notes
Chemical and Hazmat 1,000-50,000 0.1b – 1.3b Medium Medium High fatalities
Dams 100-10,000 ~100b Medium Effective High economics
Commercial (Buildings / Tourism) 100-8,000 2b – 10b High Medium High threat
Oil Refineries 10-100 0.1b -- 0.6b Low Medium Mostly economics
Electrical Grid 10-100 0.7b – 2.8b Low Medium Mostly economics
Transportation - Bridges 10-100 0.01b – 0.04b Medium Medium Mostly psychological
Transportation - Rail 100-1000 0.5b – 7.4b High Medium Mostly psychological
Water Treatment 100-1000 0.1b – 1.3b Low Medium Mostly chemicals
Defense Industry Base 10-100 ? Medium Medium DHS/DOE responsibility
Postal and Shipping 10-100 ? Medium Medium DHS responsibility
Nuclear Power Plants 0-100,000 12b – 40b Medium Medium NRC/DHS responsibility
Sector Prioritizations: Dams
FacilityStorage Capacity Inundation Area Population Jobs
Dam 6 3,964,960 1872 sq-mi 175,000 48,743
Dam 1 3,540,000 1341 sq-mi 138,055 52,125
Dam 2 2,420,000 1161 sq-mi 570,055 210,442
Dam 8 2,030,000
Dam 3 1,961,320 925 sq-mi 370,582 136,799
Dam 9 1,030,000
Dam 10 969,600
Dam 4 894,000 188 sq-mi 448,000 110,132
Dam 12 651,000 Arizona low low
Dam 7 221,600 Catastrophic fatalities
Dam 14 170,000
Dam 5 41,110 Catastrophic fatalities
Dam 13 28,640
Dam 11 20,790 Mission critical
Not selectedSelected
Consequence Analysis for Chemical Plants
Calpine PittsburgDelta Energy CenterHasa Inc.- Pittsburg
Pittsburg Power Plant
Wilbur West Power Plant
Nichols Road Power Plant
Los Medanos Energy Center
Praxair Distribution, Inc.
Loveridge Road Power Plant
Tesoro Golden Eagle Refinery
Antioch Water Treatment Plant
Air Products, Martinez-Tesoro
Pittsburg Water Treatment Plant
Polychemie Inc. - Pittsburg, CA
Ralph D. Bollman Water Treatment Plant
Criterion Catalysts and Technologies L.P.
Concord
Antioch
Pittsburg
Alamo
Walnut Creek
Bay Point
Pleasant Hill
Lafayette
Clayton
Martinez
Benicia
Moraga
Vine Hill
Waldon
Pacheco
§̈¦680UV24
UV242
UV24
Gate
Clayton
Treat
Leland
Bailey
Mai
n
Marsh Creek
A
Concord
L
Ta
ylo
r Ygnacio Vall ey
Solano
Buchanan
Cowell
Will
ow P
ass
18th
Port Chicago
Kirker
Pass
14th
Pacheco
Rai
lroad
Har
bor
Oak Grove
Waterfront
M orello
3rd
Geary
Lone Tre e
Olympic
Boyd
4th
Walnut
Somersv
ille
Danville
Monument
Civic
Olivera
E mpire M ine
Contra C
osta
Livorna
James Donlon
Rudgear
Oak Park
Oak
East
Alhambra
Chilpancingo
Arnold Industrial
Grayson
Meadow
Bancroft
Bab
el Denkin
ger
Stoneman
Grant
Donlan
Mes
a R
idge
Concord
Willow Pass
Waterfront
Contra Costa
Solano
Sacramento
Mount Diablo State ParkMount Diablo State Park
Us Naval Weapons Sta ConcordUs Naval Weapons Sta Concord
Us Naval Station Port ChicagoUs Naval Station Port Chicago
Observations
• CA OHS found the analysis useful– Much improved over previous year– Increased credibility – Sector based prioritization was considered very helpful
• Identified critical needs for future analyses:– Threat probability is still a problem– Need to better assess effectiveness of risk reduction
• Ongoing work– Develop criteria for assessment of risks– Assess risks and risk reduction effectiveness– Robust allocation models
Some Conclusions
• Risk assessment remains difficult– Too many possible attack scenarios – need screening
– Adversaries seek vulnerabilities and high impact - need improved threat and vulnerability analysis
– Probabilities of threats and attacks shift - need game sciences
• Economic impacts are critical – Indirect economic impacts often overshadow direct ones
– Public responses can create large indirect economic impacts
– Need strategy for addressing public concerns
• Risk management focus helps– Focus on what can be done, not what to worry about
– Many variables do not matter for decisions
– Eliminate clearly inferior options