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Risk analysis sampling methods in terrorist networks based on the Banzhaf value.

Encarnación Algaba1,2, Andrea Prieto1, Alejandro Saavedra-Nieves3

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Summary

This study introduces Banzhaf and Banzhaf-Owen values for analyzing terrorist networks. These methods identify dangerous individuals by considering network structure and coalition information, improving risk assessment.

Keywords:
Banzhaf valuecooperative gamesnetworksrankingsampling

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Area of Science:

  • Network analysis
  • Computational social science
  • Risk assessment

Background:

  • Terrorist networks pose significant security challenges.
  • Existing risk analysis methods often fail to capture network complexity and internal structures.
  • Understanding individual roles within terrorist organizations is crucial for effective counter-terrorism.

Purpose of the Study:

  • To introduce novel risk analysis measures, the Banzhaf and Banzhaf-Owen values, for terrorist networks.
  • To develop approximation algorithms for these new measures.
  • To compare the effectiveness of these values in identifying key actors in real-world terrorist networks.

Main Methods:

  • Application of Banzhaf and Banzhaf-Owen value calculations.
  • Development and implementation of approximation algorithms for these values.
  • Network analysis incorporating both topology (nodes, edges) and coalitional structures (hierarchies).

Main Results:

  • The Banzhaf and Banzhaf-Owen values provide a comprehensive approach to risk analysis in terrorist networks.
  • Approximation algorithms were successfully implemented for both measures.
  • Ranking of members within the Zerkani network (Paris 2015, Brussels 2016 attacks) was performed, highlighting differences between the two value measures.

Conclusions:

  • The Banzhaf and Banzhaf-Owen values offer a robust framework for identifying critical individuals in terrorist networks.
  • These measures effectively integrate network topology and coalitional information for enhanced risk assessment.
  • The study provides valuable insights for counter-terrorism strategies by offering a nuanced understanding of network roles.