Advertisement

Practical Algorithms for Destabilizing Terrorist Networks

  • Nasrullah Memon
  • Henrik Legind Larsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3975)

Abstract

This paper uses centrality measures from complex networks to discuss how to destabilize terrorist networks. We propose newly introduced algorithms for constructing hierarchy of covert networks, so that investigators can view the structure of terrorist networks / non-hierarchical organizations, in order to destabilize the adversaries. Based upon the degree centrality, eigenvector centrality, and dependence centrality measures, a method is proposed to construct the hierarchical structure of complex networks. It is tested on the September 11, 2001 terrorist network constructed by Valdis Krebs. In addition we also propose two new centrality measures i.e., position role index (which discovers various positions in the network, for example, leaders / gatekeepers and followers) and dependence centrality (which determines who is depending on whom in a network). The dependence centrality has a number of advantages including that this measure can assist law enforcement agencies in capturing / eradicating of node (terrorist) which may disrupt the maximum of the network.

Keywords

Complex Network Degree Centrality Social Network Analysis Centrality Measure Real World Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Albert, R., Barabási, A.L.: Dynamics of complex systems: scaling laws for the period of boolean networks, Physics Reviews 47 (2002)Google Scholar
  2. 2.
    Albert, R., Barabási, A.L.: Emergence of scaling in random networks. Science 286, 509–512 (1999)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Carley, K.M., Lee, J.-S., Krackhardt, D.: Destabilizing Networks. Connections 24(3), 79–92 (2002)Google Scholar
  4. 4.
    Carley, K.M., et al.: Destabilizing Dynamic Covert Networks. In: Proceedings of 8th International Command and Control Research and Technology Symposium, Conference held at National Defense War College, Washington, DC. Evidence Based Research Vienna, VA (2003)Google Scholar
  5. 5.
    Dorogovtsev, S.N., Mendes, J.F.F.: Evolution of Networks Adv. Phys. 51, 1079 (2002)Google Scholar
  6. 6.
    Farely, D.J.: Breaking Al Qaeda Cells: a Mathematical analysis of counterterrorism Operations Studies in conflict terrorism 26, 399–411 (2003)Google Scholar
  7. 7.
    Klerks, P.: The network paradigm applied to criminal organizations. Connections 24(3) (2001)Google Scholar
  8. 8.
    Krebs, V.: Mapping Terrorist Networks. Connections 24(3) (2002)Google Scholar
  9. 9.
    Latora, V., Marchiori, M.: How Science of Complex Networks can help in developing Strategy against Terrorism. Chaos, Solitons and Fractals 20, 69–75 (2004)MATHCrossRefGoogle Scholar
  10. 10.
    Nasrullah, M., Arroyo, D.O., Larsen, H.L.: Investigative Data Mining: A General Framework. In: Proceedings of International Conference on Computational Intelligence, Istanbul, Turkey, pp. 384–387 (2004)Google Scholar
  11. 11.
    Nasrullah, M., Larsen, H.L.: Practical Approaches for Analysis, Visualization and Destabilizing Terrorist Networks. In: Proceedings of ARES 2006: The First International Conference on Availability, Reliability and Security, Vienna University of Technology Austria (2006)Google Scholar
  12. 12.
    Newman, M.E.J.: The structure and function of complex networks. SIAM Review 45, 167–256 (2003)MATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Ravasz, E., Barabási, A.L.: Hierarchical organization in complex networks. Phys. Rev. E 67, 261121 (2003)CrossRefGoogle Scholar
  14. 14.
    Strogatz, S.H.: Exploring Complex Networks. Nature 410, 268–276 (2002)CrossRefGoogle Scholar
  15. 15.
    Trusina, A.S., Maslov, P.M., Sneppen, K.: Hierarchy and Anti-Hierarchy in Real and Scale Free Networks. Phys. Rev. Lett. 92, 178702 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Nasrullah Memon
    • 1
  • Henrik Legind Larsen
    • 1
  1. 1.Software Intelligence Security Research Center, Department of Software and Media TechnologyAalborg UniversityEsbjergDenmark

Personalised recommendations