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El. knyga: Mathematical Methods in Counterterrorism

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  • Formatas: PDF+DRM
  • Išleidimo metai: 25-Aug-2009
  • Leidėjas: Springer Verlag GmbH
  • Kalba: eng
  • ISBN-13: 9783211094426
  • Formatas: PDF+DRM
  • Išleidimo metai: 25-Aug-2009
  • Leidėjas: Springer Verlag GmbH
  • Kalba: eng
  • ISBN-13: 9783211094426

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Terrorism is one of the serious threats to international peace and security that we face in this decade. No nation can consider itself immune from the dangers it poses, and no society can remain disengaged from the efforts to combat it. The termcounterterrorism refers to the techniques, strategies, and tactics used in the ?ght against terrorism. Counterterrorism efforts involve many segments of so- ety, especially governmental agencies including the police, military, and intelligence agencies (both domestic and international). The goal of counterterrorism efforts is to not only detect and prevent potential future acts but also to assist in the response to events that have already occurred. A terrorist cell usually forms very quietly and then grows in a pattern sp- ning international borders, oceans, and hemispheres. Surprising to many, an eff- tive weapon, just as quiet mathematics can serve as a powerful tool to combat terrorism, providing the ability to connect the dots and reveal the organizational pattern of something so sinister. The events of 9/11 instantly changed perceptions of the wordsterrorist andn- work, especially in the United States. The international community was confronted with the need to tackle a threat which was not con ned to a discreet physical - cation. This is a particular challenge to the standard instruments for projecting the legal authority of states and their power to uphold public safety. As demonstrated by the events of the 9/11 attack, we know that terrorist attacks can happen anywhere.
Mathematical Methods in Counterterrorism: Tools and Techniques for a New Challenge
1(8)
David L. Hicks
Nasrullah Memon
Jonathan D. Farley
Torben Rosenørn
Introduction
1(1)
Organization
2(2)
Conclusion and Acknowledgements
4(5)
Part I Network Analysis
Modeling Criminal Activity in Urban Landscapes
9(24)
Patricia Brantingham
Uwe Glasser
Piper Jackson
Mona Vajihollahi
Introduction
9(2)
Background and Motivation
11(3)
Computational Criminology
11(2)
Challenges and Needs
13(1)
Modeling Paradigm
13(1)
Mastermind Framework
14(5)
Mathematical Framework
15(2)
Rapid Prototyping with Core ASM
17(1)
Interactive Design with Control State ASMs
18(1)
Mastermind: Modeling Criminal Activity
19(9)
Overview
19(1)
Agent Architecture
20(2)
Urban Landscape Model
22(2)
Space Evolution Module: ASM Model
24(2)
Lessons Learned
26(2)
Concluding Remarks
28(5)
References
29(4)
Extracting Knowledge from Graph Data in Adversarial Settings
33(22)
David Skillicorn
Characteristics of Adversarial Settings
33(1)
Sources of Graph Data
34(1)
Eigenvectors and the Global Structure of a Graph
35(1)
Visualization
36(1)
Computation of Node Properties
37(2)
Social Network Analysis (SNA)
37(1)
Principal eigenvector of the adjacency matrix
38(1)
Embedding Graphs in Geometric Space
39(13)
The Walk Laplacian of a graph
39(1)
Dimensionality reduction
40(1)
The rightmost eigenvectors
41(3)
The leftmost eigenvectors
44(2)
The `middle' eigenvectors
46(3)
Working in a lower-dimensional space
49(1)
Overlays of eigenvectors and edges
50(1)
Using correlation rather than connection
51(1)
Summary
52(3)
References
53(2)
Mathematically Modeling Terrorist Cells: Examining the Strength of Structures of Small Sizes
55(14)
Lauren McGough
``Back to Basics'': Recap of the Poset Model of Terrorist Cells
55(2)
Examining the Strength of Terrorist Cell Structures - Questions Involved and Relevance to Counterterrorist Operations
57(1)
Definition of ``Strength'' in Terms of the Poset Model
58(1)
Posets Addressed
59(1)
Algorithms Used
59(2)
Structures of Posets of Size 7: Observations and Patterns
61(4)
Implications and Applicability
65(1)
Ideas for Future Research
66(1)
Conclusion
67(2)
References
67(2)
Combining Qualitative and Quantitative Temporal Reasoning for Criminal Forensics
69(22)
Abbas K. Zaidi
Mashhood Ishaque
Alexander H. Levis
Introduction
69(2)
Temporal Knowledge Representation and Reasoning
71(1)
Point-Interval Logic
72(10)
Language and Point Graph Representation
73(3)
Operations on Point Graphs
76(1)
Inference
77(2)
Deciding Consistency
79(1)
Temper
80(2)
Using Temper for Criminal Forensics - The London Bombing
82(6)
Conclusion
88(3)
References
89(2)
Two Theoretical Research Questions Concerning the Structure of the Perfect Terrorist Cell
91(16)
Jonathan David Farley
References
102(5)
Part II Forecasting
Understanding Terrorist Organizations with a Dynamic Model
107(20)
Alexander Gutfraind
Introduction
107(2)
A Mathematical Model
109(2)
Analysis of the Model
111(3)
Discussion
114(3)
Nascent terrorist organizations
114(1)
Conditions for Victory
115(2)
Stable Equilibria
117(1)
Counter-Terrorism Strategies
117(3)
Targeting the leaders
117(2)
Encouraging desertion
119(1)
Minimization of Strength S
120(1)
Conclusions
120(1)
7 Appendix
121(6)
Proof of the theorem
122(1)
Concrete Example of Strength Minimization
123(1)
References
124(3)
Inference Approaches to Constructing Covert Social Network Topologies
127(14)
Christopher J. Rhodes
Introduction
127(1)
Network Analysis
128(1)
A Bayesian Inference Approach
129(2)
Case 1 Analysis
131(3)
Case 2 Analysis
134(4)
Conclusions
138(3)
References
139(2)
A Mathematical Analysis of Short-term Responses to Threats of Terrorism
141(20)
Edieal J. Pinker
Introduction
141(4)
Information Model
145(3)
Defensive Measures
148(4)
Analysis
152(4)
Interaction between warnings and physical deployments
152(2)
Effect of intelligence on defensive measures
154(2)
Illustrative numerical experiments
156(2)
Summary
158(3)
References
160(1)
Network Detection Theory
161(24)
James P. Ferry
Darren Lo
Stephen T. Ahearn
Aaron M. Phillips
Introduction
161(4)
Random Intersection Graphs
165(4)
Induced edge clique covers; exact quantities
166(1)
Expected subgraph counts in the constant-μ limit
166(3)
Subgraph Count Variance
169(3)
Dynamic Random Graphs
172(1)
The telegraph process
172(1)
The dynamic Erdos-Renyi process
173(1)
Tracking on Networks
173(4)
The LRDT Framework for Static Networks
174(3)
Hierarchical Hypothesis Management
177(3)
The Hypothesis Lattice
178(1)
The HHM Algorithm
178(1)
An Example
179(1)
Conclusion
180(5)
References
180(5)
Part III Communication/Interpretation
Security of Underground Resistance Movements
185(20)
Bert Hartnell
Georg Gunther
Introduction
185(1)
Best defense against optimal subversive strategies
186(4)
Best defense against random subversive strategies
190(3)
Maximizing the size of surviving components
193(3)
Ensuring that the survivor graph remains connected
196(9)
References
203(2)
Intelligence Constraints on Terrorist Network Plots
205(10)
Gordon Woo
Introduction
205(1)
Tipping Point in Conspiracy Size
206(3)
Tipping Point Examples
209(3)
Stopping Rule for Terrorist Attack Multiplicity
212(1)
Preventing Spectacular Attacks
213(2)
References
214(1)
On Heterogeneous Covert Networks
215(14)
Roy Lindelauf
Peter Borm
Herbert Hamers
Introduction
216(1)
Preliminaries
217(1)
Secrecy and Communication in Homogeneous Covert Networks
218(2)
Jemaah Islamiya Bali bombing
220(3)
A First Approach to Heterogeneity in Covert Networks
223(6)
The Optimal High Risk Interaction Pair
223(3)
Approximating Optimal Heterogeneous Covert Networks
226(2)
References
228(1)
Two Models for Semi-Supervised Terrorist Group Detection
229(24)
Fatih Ozgul
Zeki Erdem
Chris Bowerman
Introduction
229(1)
Terrorist Group Detection from Crime and Demographics Data
230(5)
COPLINK CrimeNet Explorer
230(4)
TMODS
234(1)
Offender Group Representation Model (OGRM)
235(1)
Group Detection Model (GDM)
236(1)
Offender Group Detection Model (OGDM)
237(5)
Computing Similarity Score
239(1)
Using Terrorist Modus Operandi Ontology
239(1)
Deciding Threshold
240(1)
Feature Selection
241(1)
Experiments and Evaluation
242(2)
Performance Matrix
242(1)
Testbed: Terrorist Groups Detected in Bursa
243(1)
Conclusion
244(9)
References
247(6)
Part IV Behavior
CAPE: Automatically Predicting Changes in Group Behavior
253(18)
Amy Sliva
V.S. Subrahmanian
Vanina Martinez
Gerardo Simari
Introduction
253(2)
CAPE Architecture
255(1)
SitCAST Predictions
256(2)
CONVEX and SitCAST
258(2)
The CAPE Algorithm
260(6)
The Change Table
260(2)
Learning Predictive Conditions from the Change Table
262(3)
The CAPE-Forecast Algorithm
265(1)
Experimental Results
266(1)
Related Work
267(1)
Conclusions
268(3)
References
269(2)
Interrogation Methods and Terror Networks
271(20)
Mariagiovanna Baccara
Heski Bar-Isaac
Introduction
271(3)
Related Literature
274(1)
Model
274(4)
Law Enforcement Agency
275(1)
Information Structure
276(1)
Payoffs
277(1)
The Optimal Network
278(3)
The Enforcement Agency
281(4)
Investigation Budget Allocation
282(1)
Legal Environment and Interrogation Methods
283(2)
Extensions and Conclusions
285(6)
References
290(1)
Terrorists and Sponsors. An Inquiry into Trust and Double-Crossing
291(18)
Gordon H. McCormick
Guillermo Owen
State-Terrorist Coalitions
291(4)
The Mathematical Model
295(2)
Equilibrium Strategies
297(3)
Payoff to T
300(2)
The Trust Factor
302(1)
Interpretation
303(5)
Conclusion. External Shocks
308(1)
References
308(1)
Simulating Terrorist Cells: Experiments and Mathematical Theory
309(10)
Lauren McGough
Introduction
309(1)
The Question of Theory versus Real-Life Applications
310(1)
Design
311(1)
Procedure
312(1)
Analysis and Conclusions
313(6)
References
316(3)
Part V Game Theory
A Brinkmanship Game Theory Model of Terrorism
319(14)
Francois Melese
Introduction
319(3)
The Extensive Form of the Brinkmanship Game
322(3)
Incentive Compatibility (``Credibility'') Constraints
325(3)
The Effectiveness Constraint
326(2)
The Acceptability Constraint
328(1)
Equilibrium Solution and Interpretation of the Results
328(2)
Conclusion
330(3)
References
332(1)
Strategic Analysis of Terrorism
333(16)
Daniel G. Arce
Todd Sandler
Introduction
333(2)
Strategic Substitutes and Strategic Complements in the Study of Terrorism
335(7)
Proactive Counterterrorism Measures
336(2)
Defensive Countermeasures: Globalized Threat
338(1)
Defensive Measures: No Collateral Damage
339(1)
Intelligence
340(1)
Other Cases
341(1)
Terrorist Signaling: Backlash and Erosion Effects
342(5)
Concluding Remarks
347(2)
References
347(2)
Underfunding in Terrorist Organizations
349(36)
Jacob N. Shapiro
David A. Siegel
Introduction
349(4)
Motivation
353(6)
Game
355(1)
Actors
356(3)
Model
359(2)
Game Form
359(1)
Actors
360(1)
Results
361(9)
Equilibrium Strategies
362(4)
Comparative Statics
366(4)
Discussion
370(5)
Conclusion
375(10)
References
380(5)
Part VI History of the Conference on Mathematical Methods in Counterterrorism
Personal Reflections on Beauty and Terror
385(4)
Jonathan David Farley
Shadows Strike
385(1)
The ``Thinking Man's Game''
385(2)
The Elephant: Politics
387(2)
Toward a Mathematical Theory of Counterterrorism
389