Skip to main content
SpringerLink
Log in

Dynamical Adaptation in Terrorist Cells/Networks

  • Conference paper
  • First Online:
Advanced Techniques in Computing Sciences and Software Engineering

Abstract

Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long history of their successful use in revealing the importance of various members of the network. However, modeling of covert, terrorist or criminal networks through social graph dose not really provide the hierarchical structure which exist in these networks as these networks are composed of leaders and followers etc. In this research we analyze and predict the most likely role a particular node can adapt once a member of the network is either killed or caught. The adaptation is based on computing Bayes posteriori probability of each node and the level of the said node in the network structure.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Valdis Krebs:. Connecting the dots, tracking two identified terrorists, 2002.

    Google Scholar 

  2. Jacob Levy Moreno:. Sociometry, experimental method and the science of society, an approach to a new political orientation, 1951, published by beacon house.

    Google Scholar 

  3. Cory Kutcher:. Social network analysis - linking foreign terrorist organizations, 2008.

    Google Scholar 

  4. Dil M. Akbar Hussain:. Destabilization of terrorist networks through argument driven hypothesis model, journal of software, vol. 2, no. 6, pages 22 - 29, 2007.

    Google Scholar 

  5. Bavelas A:. A mathematical model for group structures, human organization 7, pages 16 - 30, 1948.

    Google Scholar 

  6. Shaw M. E:. Group structure and the behaviour of individuals in small groups, journal of psychology, vol. 38, pages 139 - 149, 1954.

    Google Scholar 

  7. Scott J:. Social networks analysis. 2nd edition, sage publications, london, 2003.

    Google Scholar 

  8. Newman M. E. J:. A measure of betweenness centrality based on random walks, cond-mat/0309045, 2003.

    Google Scholar 

  9. Siddharth Kaza Daning Hu and Hsinchun Chen:. Dynamic social network analysis of a dark network: Identifying significant facilitators, ISI, pages 40–46, 2007.

    Google Scholar 

  10. Paramjit S. Gill and Tim B. Swartz:. Bayesian analysis of directed graphs data with applications to social networks, appl. statist. (2004) 53, part 2, pp. 249 - 260.

    MATH  Google Scholar 

  11. Wong G. Y.:. Bayesian models for directed graphs. j. am. statist. ass., 82, 140 148.

    Google Scholar 

  12. Gill P. S. and Swartz T. B.:. Statistical analyses for round robin interaction data. can. j. statist., 29, 321 331.

    Google Scholar 

  13. Gill P. S. and Swartz T. B.:. Bayesian analysis for dyadic designs in psychology.

    Google Scholar 

  14. Nowicki K. and Snijders T. A. B:. Estimation and prediction for stochastic blockstructures. j.am. statist. ass., 96, 1077 1087.

    Google Scholar 

  15. Douglas C. Montgomery and George C. Runger:. George c. runger: Applied statistics abd probability for engineers, 4th edition, isbn 978-0-471-74589-1, john wiley and sons, 2006.

    Google Scholar 

  16. John H. Koskinen and Tom A. B. Snijders:. Bayesian inference for dynamic social network data, journal of statistical planning and inference 137 3930 - 3938, 2007.

    Google Scholar 

  17. Siddarth K. Daning H. and Hsinchum Chen:. Dynamic social network analysis of a dark network: Identifying significant facilitators, proceedings of ieee international conference on intelligence and security informatics, isi 2007, new brunswick, new jersey, usa, may 23 - 24, 2007.

    Google Scholar 

  18. C. J. Rhodes and E. M. J. Keefe:. Social network topology: a bayesian approach, journal of the operational research society 58, 1605 - 1611, 2007.

    Google Scholar 

  19. Holland P. W. and Leinhardt S.:. An exponential family of probability distributions for directed graphs. j. am. statist. ass., 76, 33 65.

    Google Scholar 

  20. Oliver C. Ibe:. Fundamentals of applied probability and random processes, elsevier academics press, isbn 0-12-088508-5, 2005.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronic Systems, Aalborg University, Niels Bohrs Vej 8, 6700, Esbjerg, Denmark

    D. M. Akbar Hussain

  2. Institute of Laser and Optics (PILO), Islamabad, Pakistan

    Zaki Ahmed

Authors
  1. D. M. Akbar Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zaki Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to D. M. Akbar Hussain .

Editor information

Editors and Affiliations

  1. School of Engineering, University of Bridgeport, University Avenue 221, Bridgeport, 06604, U.S.A.

    Khaled Elleithy

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media B.V.

About this paper

Cite this paper

Hussain, D.M.A., Ahmed, Z. (2010). Dynamical Adaptation in Terrorist Cells/Networks. In: Elleithy, K. (eds) Advanced Techniques in Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3660-5_95

Download citation

  • DOI: https://doi.org/10.1007/978-90-481-3660-5_95

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-3659-9

  • Online ISBN: 978-90-481-3660-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation