
Mathematical Methods for Destabilizing Terrorist Activities
Methods and Practical Algorithms for Analysis and Visualization
Springer (Publisher)
Published on 15. June 2014
Book
Hardback
300 pages
978-3-211-99440-5 (ISBN)
Description
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.
More details
Edition
2013
Language
English
Place of publication
Vienna
Austria
Target group
Professional and scholarly
Research
Illustrations
30 farbige Abbildungen
30 colour illustrations, biography
Dimensions
Height: 0 mm
Width: 0 mm
ISBN-13
978-3-211-99440-5 (9783211994405)
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Schweitzer Classification
Content
Table of Contents.- Part 1: Understanding Terrorism,Terrorist and Terrorist Organization.- Chapter 1: Terrorism and Terrorists.- Chapter 2: Terrorist Organizations and groups.- Chapter 3: How it all begun.- Chapter 4: Investigative Data Mining.- Chapter 5: Terrorist Network Analysis.- Chapter 6: Visualizing Networks.- Chapter 7: Cohesion analysis and detecting critical regions.- Chapter 8: Extending Social Network Analysis.- Chapter 9: Detecting Hidden Hierarchy.- Chapter 10: Investigative Data Mining Tool Kit (iMiner).- Chapter 11: Practical Data Sets.