Mathematical Methods for Destabilizing Terrorist Activities
Methods and Practical Algorithms for Analysis and Visualization
(Sprache: Englisch)
This work represents the latest in mathematical and computational techniques to assist in combating terrorist cells. Achieved by quantifying threats and the effectiveness of counterterrorism operations and strategies, contributors share theories and...
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This work represents the latest in mathematical and computational techniques to assist in combating terrorist cells. Achieved by quantifying threats and the effectiveness of counterterrorism operations and strategies, contributors share theories and methodologies to generate and analyze terrorist networks and provide mathematical methods and practical algorithms for destabilizing adversaries. New developments include: A new centrality-like measure to screen networks for potential actors of interest; Detection of topological characteristics of these networks to understand structure; Measures based on efficiency of networks to identify key players; Theories to detect command structures of networks by detecting hidden hierarchies; A knowledge base of the terrorist attacks in / planned in the past, by spidering data. Results of command structure via new algorithms with SNA literature (N-Clique, K-Core, etc.) are compared. The best techniques are combined to assist intelligence agencies / law enforcement.
Klappentext zu „Mathematical Methods for Destabilizing Terrorist Activities “
The primary objective of this research is to develop the underlying theory and associated methodologies used to generate and analyze terrorist networks and propose mathematical methods and practical algorithms for destabilizing these adversaries. It aims to develop a new centrality-like measure, via extensions of several others in use to screen networks for agents of interest. Presents the theoretical bases that make this measure more amenable to terrorist networks, and their advantages. Provides a theory of detecting command structures of terrorist networks. The algorithms for detecting hidden hierarchy of terrorist network are discussed. Results of command structure obtained by using new algorithms and other centralities with related SNA literature like N-Clique, K-Core, etc. are compared. Includes new algorithms for finding direct and indirect relations in a network. Combines the most promising techniques into a prototype tool-set to assist intelligence agencies / law enforcement and others.
Inhaltsverzeichnis zu „Mathematical Methods for Destabilizing Terrorist Activities “
Part 1: Unsderstanding Terrorism,Terrorist and Terrorist OrganizationChapter 1: Terrorism and Terrorists
- Overview
- Types of Terrorist
- Terrorism and Organized Crime
- Similarities
- Dissimilarities
- Characteristics of Terrorists
- Status
- Education and Intellect
- Age
- Gender
- Appearance
- Summary
Chapter 2: Terrorist Organizations and groups
- Overview
- Terrorist Group Structure
- Tactical-level Cellular Organization
- Group Organizational Structure
- Hierarchical Structure
- Networked Structure
- Some Examples of Terrorist Organization
- Al-Qaeda
- Summary
Part 2: Mapping Terrorist Networks
Chapter 3: How it all begun
- Historical Overview
Chapter 4: Investigative Data Mining
- Overview
- Difference Between Investigative Data Mining and Traditional Data Mining
- Investigative Data Mining Tasks
- Connecting Dots to summarize links
- Limitations of Investigative Data Mining
- Variations in Literature about Investigative Data Mining
- Summary
Part 3: Terrorist Network Analysis
Chapter 5: Terrorist Network Analysis
- Overview
- Dimensions of Terrorist Networks
- Hurdles in understanding terrorist networks
- Analyzing Social Network Dynamics
- Descriptive methods
- Statistical Methods
- Simulation Methods
- Graph Theory
- Standard Centrality Measures
- Degree Centrality
- Closeness Centrality
- Betweenness Centrality
- Eigen Vector Centrality
- Statistical Measures of Network Topology
- Degree Distribution
- Clustering Coefficient
- Average Path Length
- Graphs as Models of Real-World Networks
- Summary
Chapter 6: Visualizing Networks
- Overview
- Why visualization?
- Exploring Social Network Visualization Frameworks
- The "musts" for an ideal Terrorist Visualization Framework
- Using Prefuse; as an classical example
- Design of the prefuse Toolkit
- Abstract Data
- Filtering
- Managing Visual Items: The ItemRegistry
- Actions
- ActionLists and Activities
- Rendering and Display
- The
... mehr
prefuse Library
- Summary
Part 4: Destablizing Terrorist Networks
Chapter 7: Cohesion analysis and detecting critical regions
- Overview
- Detecting Clusters
- Case Study: 9/11 Terrorist Network and affiliates
- Detecting Critical regions
- Sub group Detection
- Summary
Chapter 8: Extending Social Network Analysis
- Overview
- Position Role Index
- Efficiency of the Network
- Dependence Centrality
- Different flags to identify different situations in dependence centrality matrix
- Summary
Chapter 9: Detecting Hidden Hierarchy
- Overview
- Historical Development
- Main Steps of Detecting Hierarchy
- Case Studies
- Summary
Part 5: Software Implementation
Chapter 10: Investigative Data Mining Tool Kit (iMiner)
- Overview
- System Architecture
- Information harvesting system (IIHS)
- The Original knowledge base
- Knowledge base Strengths
- Weaknesses of Open Source Knowledge bases
- Summary
Chapter 11: Practical Data Sets
- Bali Night Club Bombing Terrorist Attack
- Dirty Bomb Plot
- WTC 1993 Bombing Plot
- September 11, 2001 Terrorist Plot
- Bojinka Terrorist Plot
- Apendices etwork Analysis
- Overview
- Position Role Index
- Efficiency of the Network
- Dependence Centrality
- Different flags to identify different situations in dependence ce
- Summary
Part 4: Destablizing Terrorist Networks
Chapter 7: Cohesion analysis and detecting critical regions
- Overview
- Detecting Clusters
- Case Study: 9/11 Terrorist Network and affiliates
- Detecting Critical regions
- Sub group Detection
- Summary
Chapter 8: Extending Social Network Analysis
- Overview
- Position Role Index
- Efficiency of the Network
- Dependence Centrality
- Different flags to identify different situations in dependence centrality matrix
- Summary
Chapter 9: Detecting Hidden Hierarchy
- Overview
- Historical Development
- Main Steps of Detecting Hierarchy
- Case Studies
- Summary
Part 5: Software Implementation
Chapter 10: Investigative Data Mining Tool Kit (iMiner)
- Overview
- System Architecture
- Information harvesting system (IIHS)
- The Original knowledge base
- Knowledge base Strengths
- Weaknesses of Open Source Knowledge bases
- Summary
Chapter 11: Practical Data Sets
- Bali Night Club Bombing Terrorist Attack
- Dirty Bomb Plot
- WTC 1993 Bombing Plot
- September 11, 2001 Terrorist Plot
- Bojinka Terrorist Plot
- Apendices etwork Analysis
- Overview
- Position Role Index
- Efficiency of the Network
- Dependence Centrality
- Different flags to identify different situations in dependence ce
... weniger
Bibliographische Angaben
- 2014, 300 Seiten, 30 farbige Abbildungen, Maße: 0,1 cm, Gebunden, Englisch
- Ed. by Memon, Nasrullah; Wiil, Uffe Kock
- Herausgegeben: Nasrullah Memon, Uffe Kock Wiil
- Verlag: Springer
- ISBN-10: 3211994408
- ISBN-13: 9783211994405
Sprache:
Englisch
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