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FOREWORD BY SEN. MARK WARNER
1. 1 NEW RULES
2. 2 COMBATING MISINFORMATION AND DISINFORMATION
3. 3 HARDEN NETWORKS, WEAPONS SYSTEMS, AND IOT (INTERNET OF THINGS)
4. 4 REALIGN DEFENSE SPENDING
5. 5 PRESIDENTIAL/GOVERNMENT LEADERSHIP
FOREWORD BY PROF. ANDREW ODLYZKO
1. 1 INTRODUCTION
2. 2 THE TECHNOLOGISTS' SKEWED VIEW OF THE WORLD
3. 3 THE STATE OF THE WORLD
4. 4 THREATS
5. 5 HUMANSPACE VERSUS CYBERSPACE
6. 6 PLUSES AND MINUSES OF NATURAL STUPIDITY
7. 7 SMART AND STUPID CRIMINALS
8. 8 THE CYBERCRIME ECOSYSTEM
9. 9 BLACK SWANS VERSUS LONG TAILS
10. 10 NEGLECT OF OBVIOUS SECURITY MEASURES
11. 11 SURVEILLANCE CAPITALISM AND LOSS OF PRIVACY
12. 12 THE DECEPTIVELY TRANSPARENT BUT OPAQUE WORLD
13. 13 THE VIRTUES OF MESSINESS
14. 14 SPEED, REACH, AND COST FOR OFFENSE AND DEFENSE
15. 15 THE INCREASINGLY AMBIGUOUS NOTION OF SECURITY
16. 16 CONCLUSIONS
17. ACKNOWLEDGMENTS
18. REFERENCES
PREFACE
HOW TO USE THIS BOOK
ABOUT THE COMPANION WEBSITE
1 ORIGINS OF CRITICAL INFRASTRUCTURE PROTECTION
1. 1.1 RECOGNITION
2. 1.2 NATURAL DISASTER RECOVERY
3. 1.3 DEFINITIONAL PHASE
4. 1.4 PUBLIC–PRIVATE COOPERATION
5. 1.5 FEDERALISM: WHOLE OF GOVERNMENT
6. 1.6 RISE OF THE FRAMEWORK
7. 1.7 IMPLEMENTING A RISK STRATEGY
8. 1.8 ANALYSIS
9. 1.9 EXERCISES
10. 1.10 DISCUSSIONS
11. REFERENCES
2 RISK STRATEGIES
1. 2.1 EXPECTED UTILITY THEORY
2. 2.2 PRA AND FAULT TREES
3. 2.3 MRBA AND RESOURCE ALLOCATION
4. 2.4 CYBER KILL CHAINS ARE FAULT TREES
5. 2.5 PRA IN THE SUPPLY CHAIN
6. 2.6 PROTECTION VERSUS RESPONSE
7. 2.7 THREAT IS AN OUTPUT
8. 2.8 BAYESIAN BELIEF NETWORKS
9. 2.9 RISK OF A NATURAL DISASTER
10. 2.10 EARTHQUAKES
11. 2.11 BLACK SWANS AND RISK
12. 2.12 BLACK SWAN FLOODS
13. 2.13 ARE NATURAL DISASTERS GETTING WORSE?
14. 2.14 BLACK SWAN AL QAEDA ATTACKS
15. 2.15 BLACK SWAN PANDEMIC
16. 2.16 RISK AND RESILIENCE
17. 2.17 EXERCISES
18. 2.18 DISCUSSIONS
19. REFERENCES
3 THEORIES OF CATASTROPHE
1. 3.1 NORMAL ACCIDENT THEORY (NAT)
2. 3.2 BLOCKS AND SPRINGS
3. 3.3 BAK'S PUNCTUATED EQUILIBRIUM THEORY
4. 3.4 TRAGEDY OF THE COMMONS (TOC)
5. 3.5 THE US ELECTRIC POWER GRID
6. 3.6 PARADOX OF ENRICHMENT (POE)
7. 3.7 COMPETITIVE EXCLUSION PRINCIPLE (CEP)
8. 3.8 PARADOX OF REDUNDANCY (POR)
9. 3.9 RESILIENCE OF COMPLEX INFRASTRUCTURE SYSTEMS
10. 3.10 EMERGENCE
11. 3.11 EXERCISES
12. 3.12 DISCUSSIONS
13. REFERENCES
4 COMPLEX CIKR SYSTEMS
1. 4.1 CIKR AS NETWORKS
2. 4.2 CASCADING CIKR SYSTEMS
3. 4.3 NETWORK FLOW RISK AND RESILIENCE
4. 4.4 PARADOX OF REDUNDANCY
5. 4.5 NETWORK RISK
6. 4.6 THE FRAGILITY FRAMEWORK
7. 4.7 EXERCISES
8. 4.8 DISCUSSIONS
9. REFERENCES
5 COMMUNICATIONS
1. 5.1 EARLY YEARS
2. 5.2 REGULATORY STRUCTURE
3. 5.3 THE ARCHITECTURE OF THE COMMUNICATIONS SECTOR
4. 5.4 RISK AND RESILIENCE ANALYSIS
5. 5.5 CELLULAR NETWORK THREATS
6. 5.6 ANALYSIS
7. 5.7 EXERCISES
8. 5.8 DISCUSSIONS
9. REFERENCES
6 INTERNET
1. 6.1 THE INTERNET MONOCULTURE
2. 6.2 ANALYZING THE AUTONOMOUS SYSTEM NETWORK
3. 6.3 THE RFC PROCESS
4. 6.4 THE INTERNET OF THINGS (IOT)
5. 6.5 COMMERCIALIZATION
6. 6.6 THE WORLD WIDE WEB
7. 6.7 INTERNET GOVERNANCE
8. 6.8 INTERNATIONALIZATION
9. 6.9 REGULATION AND BALKANIZATION
10. 6.10 EXERCISES
11. 6.11 DISCUSSIONS
7 CYBER THREATS
1. 7.1 THREAT SURFACE
2. 7.2 BASIC VULNERABILITIES
3. 7.3 BOTNETS
4. 7.4 CYBER RISK ANALYSIS
5. 7.5 CYBER INFRASTRUCTURE RISK
6. 7.6 ANALYSIS
7. 7.7 EXERCISES
8. 7.8 DISCUSSIONS
9. REFERENCES
8 INFORMATION TECHNOLOGY (IT)
1. 8.1 PRINCIPLES OF IT SECURITY
2. 8.2 ENTERPRISE SYSTEMS
3. 8.3 CYBER DEFENSE
4. 8.4 BASICS OF ENCRYPTION
5. 8.5 ASYMMETRIC ENCRYPTION
6. 8.6 PKI
7. 8.7 COUNTERMEASURES
8. 8.8 EXERCISES
9. 8.9 DISCUSSIONS
10. REFERENCES
9 HACKING SOCIAL NETWORKS
1. 9.1 WEB 2.0 AND THE SOCIAL NETWORK
2. 9.2 SOCIAL NETWORKS AMPLIFY MEMES
3. 9.3 TOPOLOGY MATTERS
4. 9.4 COMPUTATIONAL PROPAGANDA
5. 9.5 THE ECHO CHAMBER
6. 9.6 BIG DATA ANALYTICS
7. 9.7 GDPR
8. 9.8 SOCIAL NETWORK RESILIENCE
9. 9.9 THE REGULATED WEB
10. 9.10 EXERCISES
11. 9.11 DISCUSSIONS
12. REFERENCES
10 SUPERVISORY CONTROL AND DATA ACQUISITION
1. 10.1 WHAT IS SCADA?
2. 10.2 SCADA VERSUS ENTERPRISE COMPUTING DIFFERENCES
3. 10.3 COMMON THREATS
4. 10.4 WHO IS IN CHARGE?
5. 10.5 SCADA EVERYWHERE
6. 10.6 SCADA RISK ANALYSIS
7. 10.7 NIST‐CSF
8. 10.8 SFPUC SCADA REDUNDANCY
9. 10.9 INDUSTRIAL CONTROL OF POWER PLANTS
10. 10.10 ANALYSIS
11. 10.11 EXERCISES
12. 10.12 DISCUSSIONS
11 WATER AND WATER TREATMENT
1. 11.1 FROM GERMS TO TERRORISTS
2. 11.2 FOUNDATIONS: SDWA OF 1974
3. 11.3 THE BIOTERRORISM ACT OF 2002
4. 11.4 THE ARCHITECTURE OF WATER SYSTEMS
5. 11.5 THE HETCH HETCHY NETWORK
6. 11.6 RISK ANALYSIS
7. 11.7 HETCH HETCHY INVESTMENT STRATEGIES
8. 11.8 HETCH HETCHY THREAT ANALYSIS
9. 11.9 ANALYSIS
10. 11.10 EXERCISES
11. 11.11 DISCUSSIONS
12. REFERENCES
12 ENERGY
1. 12.1 ENERGY FUNDAMENTALS
2. 12.2 REGULATORY STRUCTURE OF THE ENERGY SECTOR
3. 12.3 INTERDEPENDENT COAL
4. 12.4 THE RISE OF OIL AND THE AUTOMOBILE
5. 12.5 ENERGY SUPPLY CHAINS
6. 12.6 THE CRITICAL GULF OF MEXICO CLUSTER
7. 12.7 THREAT ANALYSIS OF THE GULF OF MEXICO SUPPLY CHAIN
8. 12.8 NETWORK ANALYSIS OF THE GULF OF MEXICO SUPPLY CHAIN
9. 12.9 THE KEYSTONEXL PIPELINE CONTROVERSY
10. 12.10 THE NATURAL GAS SUPPLY CHAIN
11. 12.11 ANALYSIS
12. 12.12 EXERCISES
13. 12.13 DISCUSSIONS
14. REFERENCES
13 ELECTRIC POWER
1. 13.1 THE GRID
2. 13.2 FROM DEATH RAYS TO VERTICAL INTEGRATION
3. 13.3 OUT OF ORDERS 888 AND 889 COMES CHAOS
4. 13.4 THE NORTH AMERICAN GRID
5. 13.5 ANATOMY OF A BLACKOUT
6. 13.6 THREAT ANALYSIS
7. 13.7 RISK ANALYSIS
8. 13.8 ANALYSIS OF WECC96
9. 13.9 ANALYSIS
10. 13.10 EXERCISES
11. 13.11 DISCUSSIONS
12. REFERENCES
14 HEALTHCARE AND PUBLIC HEALTH
1. 14.1 THE SECTOR PLAN
2. 14.2 ROEMER'S MODEL
3. 14.3 THE COMPLEXITY OF PUBLIC HEALTH
4. 14.4 RISK ANALYSIS OF HPH SECTOR
5. 14.5 BIOTERRORISM
6. 14.6 EPIDEMIOLOGY
7. 14.7 PREDICTING PANDEMICS
8. 14.8 BIO‐SURVEILLANCE
9. 14.9 NETWORK PANDEMICS
10. 14.10 THE WORLD TRAVEL NETWORK
11. 14.11 EXERCISES
12. 14.12 DISCUSSIONS
13. REFERENCES
15 TRANSPORTATION
1. 15.1 TRANSPORTATION UNDER TRANSFORMATION
2. 15.2 THE ROAD TO PROSPERITY
3. 15.3 RAIL
4. 15.4 AIR
5. 15.5 AIRPORT GAMES
6. 15.6 EXERCISES
7. 15.7 DISCUSSIONS
8. REFERENCES
16 SUPPLY CHAINS
1. 16.1 THE WORLD IS FLAT, BUT TILTED
2. 16.2 THE WORLD TRADE WEB
3. 16.3 RISK ASSESSMENT
4. 16.4 ANALYSIS
5. 16.5 EXERCISES
6. 16.6 DISCUSSIONS
7. REFERENCES
17 BANKING AND FINANCE
1. 17.1 THE FINANCIAL SYSTEM
2. 17.2 FINANCIAL NETWORKS
3. 17.3 VIRTUAL CURRENCY
4. 17.4 HACKING THE FINANCIAL NETWORK
5. 17.5 HOT MONEY
6. 17.6 THE END OF STIMULUS?
7. 17.7 FRACTAL MARKETS
8. 17.8 EXERCISES
9. 17.9 DISCUSSIONS
10. REFERENCES
18 STRATEGIES FOR A NETWORKED NATION
1. 18.1 WHOLE OF GOVERNMENT
2. 18.2 RISK AND RESILIENCE
3. 18.3 COMPLEX AND EMERGENT CIKR
4. 18.4 COMMUNICATIONS AND THE INTERNET
5. 18.5 INFORMATION TECHNOLOGY (IT)
6. 18.6 SURVEILLANCE CAPITALISM
7. 18.7 INDUSTRIAL CONTROL SYSTEMS
8. 18.8 ENERGY AND POWER
9. 18.9 GLOBAL PANDEMICS
10. 18.10 TRANSPORTATION AND SUPPLY CHAINS
11. 18.11 BANKING AND FINANCE
12. 18.12 DISCUSSIONS
APPENDIX A: MATH: PROBABILITY PRIMER
1. A.1 A PRIORI PROBABILITY
2. A.2 A POSTERIORI PROBABILITY
3. A.3 RANDOM NETWORKS
4. A.4 CONDITIONAL PROBABILITY
5. A.5 BAYESIAN NETWORKS
6. A.6 BAYESIAN REASONING
7. REFERENCES
8. FURTHER READING
APPENDIX B: MATH: RISK AND RESILIENCE
1. B.1 EXPECTED UTILITY THEORY
2. B.2 BAYESIAN ESTIMATION
3. B.3 EXCEEDENCE AND PML RISK
4. B.4 NETWORK RISK
5. B.5 MODEL‐BASED RISK ANALYSIS (MBRA)
6. REFERENCES
APPENDIX C: MATH: SPECTRAL RADIUS
1. C.1 NETWORK AS MATRIX
2. C.2 MATRIX DIAGONALIZATION
3. C.3 RELATIONSHIP TO RISK AND RESILIENCE
4. REFERENCE
APPENDIX D: MATH: TRAGEDY OF THE COMMONS
1. D.1 LOTKA–VOLTERRA MODEL
2. D.2 HOPF–HOLLING MODEL
APPENDIX E: MATH: THE DES AND RSA ALGORITHM
1. E.1 DES ENCRYPTION
2. E.2 RSA ENCRYPTION
APPENDIX F: GLOSSARY
INDEX
END USER LICENSE AGREEMENT

List of Tables

Chapter 1
1. TABLE 1.1 The basic critical infrastructure sectors (8) defined by PDD‐63 (1998)...
2. TABLE 1.2 CIKR (14) as of 2003
3. TABLE 1.3 CIKR (16) and responsibilities as defined by HSPD‐7
4. TABLE 1.4 CIKR as defined by PPD‐21 (2013)
5. TABLE 1.5 Selection of CIKR assets
6. TABLE 1.6 Some common high‐ and low‐risk hazards are classified according to thei...
Chapter 2
1. TABLE 2.1 The parameters for the threat–asset pairs in Figure 2.1 include T, V, a...
2. TABLE 2.2 Inputs and analysis of the hospital fault tree in Figure 2.3 shows inve...
3. TABLE 2.3 Inputs and resource allocation calculations minimization risk by reduci...
4. TABLE 2.4 Hazards may be classified as high‐ or low‐risk hazards by the fractal d...
Chapter 4
1. TABLE 4.1 Cascade failure results for increases in parameters spectral radius, vu...
2. TABLE 4.2 Constants for the 11 networks analyzed in Figure 4.7 and critical point...
3. TABLE 4.3 Fractal dimension of cascades in the SEPTA network
4. TABLE 4.4 Change in allocation is abrupt when the attacker budget exceeds $7098
5. TABLE 4.5 Example of scoring the Hodges Fragility Framework
Chapter 5
1. TABLE 5.1 Evolution of cellular telephony
Chapter 6
1. TABLE 6.1 A sampling of the most common usernames and passwords that are rarely c...
Chapter 7
1. TABLE 7.1 Input values for the general fault tree model of Figure 7.7 are used to...
Chapter 8
1. TABLE 8.1 EXCLUSIVE‐OR logic: Only one of the two operands can be 1 in order to p...
2. TABLE 8.2 Sample countermeasures to vulnerabilities typical found in enterprise s...
Chapter 9
1. TABLE 9.1 Resilience score for social network analysis using the Hodges conceptua...
Chapter 10
1. TABLE 10.1 Checklist for the protection step of the NIST‐CSF is composed of acces...
2. TABLE 10.2 Input and output values used in Figure 10.6 to evaluate risk reduction...
3. TABLE 10.3 Department of Energy's 21 steps to SCADA security are easy to follow...
Chapter 11
1. TABLE 11.1 These contaminants are regulated per the 1962 Public Health Service st...
2. TABLE 11.2 The 1996 SDWA amendments require US EPA to enforce the following
3. TABLE 11.3 Input data for the top five assets in the MBRA network model of Hetch ...
4. TABLE 11.4 Hypothetical input values for the fault tree of Figure 11.7 indicates ...
5. TABLE 11.5 Most of $600 million is allocated to harden pipelines against earthqua...
Chapter 12
1. TABLE 12.1 Energy density of familiar fuels: Uranium‐235 is off the scale, while ...
2. TABLE 12.2 Rank, name, and location of the most productive refineries in the Gulf...
3. TABLE 12.3 Allocation of $300 million reduces energy fault tree risk from $4484 m...
4. TABLE 12.4 The largest NG pipelines are more than 10,000 miles long and move over...
Chapter 14
1. TABLE 14.1 An investment of $100 million reduces risk to less than 10% and focuse...
2. TABLE 14.2 The major causes of death as reported on a death certificate are not t...
Chapter 15
1. TABLE 15.1 Commuter/light rail systems are very fragile, even though they have lo...
2. TABLE 15.2 There have been 582 airliner deaths due to suicide, sabotage, and terr...
Chapter 16
1. TABLE 16.1 Top 10 countries in the WTW ranked by network properties generally ind...
Appendix A
1. TABLE A.1 There are 16 possible combinations of H and T in four coin tosses
2. TABLE A.2 Pascal's triangle yields the probability of 0, 1, 2, 3, 4, … H's in fou...
Appendix B
1. TABLE B.1 This spreadsheet of 2007 raw data and EP calculations was used to produ...
2. TABLE B.2 Spreadsheet containing SARS data and calculations needed to convert tim...

List of Illustrations

Chapter 1
1. FIGURE 1.1 The structure of the cybersecurity and infrastructure protection ...
2. FIGURE 1.2 Two frameworks for qualitative risk management—one for physical a...
3. FIGURE 1.3 A resilience triangle is formed by a collapse followed by recover...
4. FIGURE 1.4 Some hazards are low risk and some are high risk. Risk increases ...
Chapter 2
1. FIGURE 2.1 The fundamental unit of risk is the threat–asset pair as illustra...
2. FIGURE 2.2 Risk and return on investment decline after a modest investment i...
3. FIGURE 2.3 AND fault tree for the hypothetical hospital power supply: redund...
4. FIGURE 2.4 Return on investment analysis for the redundant hospital power mo...
5. FIGURE 2.5 A fault tree model of a single trusted path from a user to data c...
6. FIGURE 2.6 A multipath kill chain connects paths with an OR gate and replica...
7. FIGURE 2.7 MBRA's network model of the hospital redundant power source requi...
8. FIGURE 2.8 Bayesian network model of threat consists of three propositions: ...
9. FIGURE 2.9 The Gutenberg–Richter law for relating the number of earthquakes ...
10. FIGURE 2.10 Long‐tailed exceedence probability curves: one for high‐risk haz...
11. FIGURE 2.11 Exceedence probability—in x–y coordinates and log(x)–log(y) coor...
12. FIGURE 2.12 Exceedence probability of financial consequences from US natural...
13. FIGURE 2.13 Fractal dimension of the Levy flight of SARS as it spread to 29 ...
14. FIGURE 2.14 The exceedence probability distributions for consequence, distan...
Chapter 3
1. FIGURE 3.1 Consequence exceedence for all known nuclear power accidents (195...
2. FIGURE 3.2 The six‐block apparatus connected by springs illustrates how a si...
3. FIGURE 3.3 Bak's sand pile experiment simulates a landslide, but it has beco...
4. FIGURE 3.4 State space diagrams of three tragedy of the commons scenarios: s...
5. FIGURE 3.5 State space diagrams reveal a system's sustainability or lack of ...
6. FIGURE 3.6 Two state space diagrams of the electric power grid tragedy of co...
7. FIGURE 3.7 Economic declines and time to next decline are punctuated events ...
8. FIGURE 3.8 State space diagram of homeownership from the Great Depression to...
9. FIGURE 3.9 Probability estimates of the time between subsequent events are b...
10. FIGURE 3.10 Most CIKR sectors form industrial commons around value chains as...
Chapter 4
1. FIGURE 4.1 The complex CIKR system network of the Washington, DC, drinking w...
2. FIGURE 4.2 CIKR networks are typically random, scale‐free, or clustered. (a)...
3. FIGURE 4.3 Forest fires are simulated as a grid containing cells that are ei...
4. FIGURE 4.4 Results of the forest fire simulation for two scenarios: (a) freq...
5. FIGURE 4.5 This cascade frequency heat map of a small microgrid section of t...
6. FIGURE 4.6 Exceedence probability for small vulnerability network nodes obey...
7. FIGURE 4.7 Fractal dimension of cascade failures in a CIKR network declines ...
8. FIGURE 4.8 The normalized cascade resilience metric separates networks into ...
9. FIGURE 4.9 Heat map display results of analysis of the LA Metro railway netw...
10. FIGURE 4.10 Risk dramatically increases when critical nodes are attacked in ...
11. FIGURE 4.11 An illustration of Braess's paradox in network flows: removing a...
12. FIGURE 4.12 Robustness is a measure of the fraction of nodes and links that ...
13. FIGURE 4.13 MBRA model of the crude oil transmission pipeline system in the ...
14. FIGURE 4.14 PML risk profiles for the crude oil CIKR network of Figure 4.13 ...
15. FIGURE 4.15 MBRA model of the flow network of Figure 4.11 layered on a map, ...
16. FIGURE 4.16 The diminishing returns curves for prevention, response, and thr...
17. FIGURE 4.17 Risk ranking and calculated results after allocation of $1500 to...
18. FIGURE 4.18 The Hodges Fragility Conceptual Framework defines fragility in t...
19. FIGURE 4.19 The Hodges framework is isomorphic to a fault tree where dimensi...
Chapter 5
1. FIGURE 5.1 The structure of US governmental agencies involved in the regulat...
2. FIGURE 5.2 The 1996 Telecommunications Act deregulated the communications se...
3. FIGURE 5.3 The architecture of the communications sector includes landlines,...
4. FIGURE 5.4 Major carrier hotels within the United States form the backbone o...
5. FIGURE 5.5 Human‐caused hazard fault tree risk model for the communications ...
6. FIGURE 5.6 Telephone outages reported by Kuhn indicate the US communications...
7. FIGURE 5.7 Critical factor analysis and resilience of the top 30 telecom rou...
8. FIGURE 5.8 The major submarine cables circling the globe carry most of the c...
Chapter 6
1. FIGURE 6.1 The DNS is a tree‐shaped network of Internet usernames and number...
2. FIGURE 6.2 Example of an email message as it travels through the Internet.
3. FIGURE 6.3 The top 500 autonomous system servers in the Internet, circa 2004...
4. FIGURE 6.4 Core of the AS500 Internet circa 2004 contained the most connecte...
5. FIGURE 6.5 The ISO/OSI standard protocol stack for the Internet consists of ...
6. FIGURE 6.6 The core of Internet governance circa 2010 included W3C, ISOC, IE...
Chapter 7
1. FIGURE 7.1 The exceedence probability and PML risk profile of a sample of 21...
2. FIGURE 7.2 The concept of an attack surface or surfaces where computer secur...
3. FIGURE 7.3 This “family tree” shows the heritage of some of the malware deri...
4. FIGURE 7.4 TCP/IP is intrinsically flawed because of its simplicity.
5. FIGURE 7.5 Buffer overflow exploits enter a computer as data but overwrites ...
6. FIGURE 7.6 DDoS recruits innocent zombies to participate in a denial‐of‐serv...
7. FIGURE 7.7 Common threat–asset pairs in a general fault tree of cyber threat...
8. FIGURE 7.8 ROI analysis of the general fault tree model for the values shown...
9. FIGURE 7.9 AS2000: The top 2000 autonomous systems of the global Internet fo...
10. FIGURE 7.10 Result of four simulations shows hub hardening to be 3.7 times a...
Chapter 8
1. FIGURE 8.1 The architecture of a trusted computing base (TCB) consists of se...
2. FIGURE 8.2 A detailed view of a typical TCB and the security technologies in...
3. FIGURE 8.3 RSA encryption produces a seemingly random stream of codewords fr...
4. FIGURE 8.4 Screen display showing “randomized” ciphertext output from the RS...
5. FIGURE 8.5 An Example of PKI: Alice sends Msg_to_Bob to Bob. Issuing certifi...
Chapter 9
1. FIGURE 9.1 Forms of harassment experienced on Wikimedia.
2. FIGURE 9.2 The nonuniform structure of a piece of the Facebook.com social ne...
3. FIGURE 9.3 The topological structure of a social network determines how fast...
4. FIGURE 9.4 Filter bubbles are managed by software that rewards users with co...
5. FIGURE 9.5 A typical CNN contains many layers of hidden neurons and robust i...
6. FIGURE 9.6 The Hodges conceptual framework adapted to social network resilie...
Chapter 10
1. FIGURE 10.1 This diagram shows a simple view of a typical SCADA system and i...
2. FIGURE 10.2 The 132‐mile north‐to‐south Pacific Pipeline delivers crude oil ...
3. FIGURE 10.3 Most SCADA systems are open to access by a number of partners an...
4. FIGURE 10.4 General fault tree of possible vulnerabilities of a typical SCAD...
5. FIGURE 10.5 Major nodes of the SFPUC water SCADA network are connected by la...
6. FIGURE 10.6 Fault tree of the three most critical nodes with hypothetical th...
7. FIGURE 10.7 An industrial control system for control of power plants connect...
8. FIGURE 10.8 PML risk due to cascading before and after optimal allocation of...
9. FIGURE 10.9 Top plot is damage versus recovery time. Bottom plot is percent ...
10. FIGURE 10.10 Top plot is node cascade resilience before an investment of $50...
Chapter 11
1. FIGURE 11.1 Typical community water systems are vertically integrated natura...
2. FIGURE 11.2 The Hetch Hetchy water and power supply network starts in the He...
3. FIGURE 11.3 Flow resilience analysis shows the Hetch Hetchy network is modes...
4. FIGURE 11.4 Simulation of downstream cascades caused by a random failure of ...
5. FIGURE 11.5 Risk versus investment in both vulnerability reduction (preventi...
6. FIGURE 11.6 Results of Stackelberg optimization of defender and attacker all...
7. FIGURE 11.7 A fault tree model of Hetch Hetchy critical nodes identifies the...
8. FIGURE 11.8 Risk reduction and vulnerability versus investment shows that ri...
Chapter 12
1. FIGURE 12.1 Most energy consumed in the US United States comes from coal, na...
2. FIGURE 12.2 Past, present, and future energy consumption in the United State...
3. FIGURE 12.3 BNSF railway network connects the largest source of coal in the ...
4. FIGURE 12.4 Simplified supply chain model of NG and petroleum energy infrast...
5. FIGURE 12.5 Petroleum Administration for Defense Districts (PADDs) are still...
6. FIGURE 12.6 Pipelines are “multiplexed” by combining different products on t...
7. FIGURE 12.7 Refined petroleum products flow from the Gulf of Mexico oil fiel...
8. FIGURE 12.8 Equipment failure and human error are the top refinery hazards....
9. FIGURE 12.9 Equipment failure, corrosion, operational accidents, and aging a...
10. FIGURE 12.10 Lightning/static electricity, operational/reaction accidents, a...
11. FIGURE 12.11 Linden Station is the focal point of the massive storage facili...
12. FIGURE 12.12 General fault tree model of probable threat–asset pairs in the ...
13. FIGURE 12.13 The core of the Gulf of Mexico oil field network is centered on...
14. FIGURE 12.14 The 10,600 mile Transco Pipeline carries liquid natural gas (LN...
Chapter 13
1. FIGURE 13.1 The five major components of the power grid are generation, tran...
2. FIGURE 13.2 Power outages in the United States increased in number and size ...
3. FIGURE 13.3 Vertically integrated power companies have been broken into olig...
4. FIGURE 13.4 Many layers of regulation shape the Grid: Congress, FERC, NERC, ...
5. FIGURE 13.5 Major power grid interconnect components, reliability coordinato...
6. FIGURE 13.6 The Grid must obey Kirchhoff's law by adjusting inflows to equal...
7. FIGURE 13.7 The 2003 Blackout started with reports from FirstEnergy (dark), ...
8. FIGURE 13.8 MBRA fault tree analysis of red team threats invests most in pro...
9. FIGURE 13.9 Threat analysis risk declines faster than vulnerability, because...
10. FIGURE 13.10 The Western power grid of 1996 (WECC96) contained a number of c...
11. FIGURE 13.11 The WECC96 power grid's blocking nodes hold the grid together a...
Chapter 14
1. FIGURE 14.1 Roemer's model is a simplified model of the public health sector...
2. FIGURE 14.2 State, local, and federal government and healthcare spending is ...
3. FIGURE 14.3 Fault tree analysis of public health sector risk focuses on thre...
4. FIGURE 14.4 A relatively small investment dramatically reduces risk because ...
5. FIGURE 14.5 The number of infected people due to the SARS pandemic obeyed a ...
6. FIGURE 14.6 The SARS pandemic formed a social network that spanned 29 countr...
7. FIGURE 14.7 The spread of SARS within the United States and globally was abr...
8. FIGURE 14.8 State diagrams of SIR and SIS epidemics differ—under certain con...
9. FIGURE 14.9 The four first‐order blocking nodes of the 9/11 terrorist social...
10. FIGURE 14.10 The OpenFlight100 network shown here with n = 100 airports and
Chapter 15
1. FIGURE 15.1 The Department of Transportation is the sector‐specific agency f...
2. FIGURE 15.2 The intermodal transportation system of the United States consis...
3. FIGURE 15.3 The cost of building and maintaining the 50+ year‐old Interstate...
4. FIGURE 15.4 The Interstate Highway System forms a transportation network con...
5. FIGURE 15.5 Railroad technology was one of the earliest examples of technolo...
6. FIGURE 15.6 Bay Area Rapid Transit (BART) is a light rail commuter train ser...
7. FIGURE 15.7 The casualty rate among all airlines carrying 14 or more people ...
8. FIGURE 15.8 The primary airports and routes of the US domestic market form a...
9. FIGURE 15.9 GUARDS is randomizing software that uses game theory to allocate...
10. FIGURE 15.10 Bayesian belief network for airport security uses evidence to d...
Chapter 16
1. FIGURE 16.1 The largest ports in the world are mostly located in Asia. (a) L...
2. FIGURE 16.2 A typical optimized supply chain contains bottlenecks known as h...
3. FIGURE 16.3 The GDP of the United States, the European Union (EU), and China...
4. FIGURE 16.4 The World Trade Web is a network of 178 nations (nodes) and thei...
5. FIGURE 16.5 Risk ranking in MSRAM considers vulnerability and consequence.
6. FIGURE 16.6 PROTECT uses Stackelberg competition to allocate limited resourc...
Chapter 17
1. FIGURE 17.1 The Federal Reserve (Fed) and US Department of Treasury (Treasur...
2. FIGURE 17.2 Money flows from the Treasury to the Fed and then on to the Fede...
3. FIGURE 17.3 The Fed balance sheet expanded at an alarming rate following the...
4. FIGURE 17.4 The 3‐D secure payment protocol enables online e‐commerce using ...
5. FIGURE 17.5 Two different forms of payment using virtual currency. (a) PayPa...
6. FIGURE 17.6 Transactions in the UCSD study span the globe.
7. FIGURE 17.7 Hot money flows from low interest rate economies to high interes...
8. FIGURE 17.8 Simulation of the nonlinear effects of economic expansion on GDP...
9. FIGURE 17.9 The S&P 500 index crashed in October 1987. Log‐periodic waves ar...
10. FIGURE 17.10 The S&P 500 index from July 1985 to October 26, 1987, is shown ...
Chapter 18
1. FIGURE 18.1 Rewiring the network of Figure 10.7 to reduce PML risk improves ...
Appendix A
1. FIGURE A.1 Probability distribution for the number of heads occurring in fou...
2. FIGURE A.2 A random network contains nodes with a binomial degree distributi...
3. FIGURE A.3 A tabular model of Pascal's ideal world of mathematical precision...
4. FIGURE A.4 A Bayesian network (BN) model of threat. (a–c) Prior beliefs of a...
Appendix B
1. FIGURE B.1 The computation tree of the BN in Chapter 2 contains all possible...
2. FIGURE B.2 Comparison of probability distribution, ranked exceedence probabi...
3. FIGURE B.3 Forest fires in Southern California are high risk according to th...
4. FIGURE B.4 Number of people who contracted SARS during an epidemic that star...
5. FIGURE B.5 Models of threat, vulnerability, and consequence used by MBRA att...
6. FIGURE B.6 Network model of major Amtrak routes in the United States. Nodes ...
7. FIGURE B.7 Exceedence probability of cascade episodes is obtained by simulat...
Appendix C
1. FIGURE C.1 The flow network of Chapter 4 as it is represented in a computer ...

CRITICAL INFRASTRUCTURE PROTECTION IN HOMELAND SECURITY

Defending a Networked Nation