An innovative approach for identification of pivotal node in terrorist network using promethee method (an anti-terrorism approach)

  • Authors

    • Saurabh Singh
    • Shashikant Verma
    • Akhilesh Tiwari
    2018-01-27
    https://doi.org/10.14419/ijet.v7i1.8828
  • Terrorist Networks, Social Networks, Social Network Analysis (SNA), Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE), Centrality, Betweenness Centrality, Closeness Centrality, Eigenvector Centrality, PageRank Centrality, Eff

  • Terrorist network analysis is vital for intelligence analysis and for deriving useful information from available raw data. Computer Science and Graph Theory provide instructive tools for the study and graphical interpretation of these networks. In this paper, we examine the 26/11 Mumbai attack terrorist network dataset and employ the Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) for identification of key node on the terrorist network. PROMETHEE is an effective multi-criteria decision-making model. It provides a framework to find the most suitable alternative by integrating the quantitative and qualitative factors to the decision problem and facilitates easy computation. From the 26/11 Mumbai attacks data set of terrorist network. It is found that out of several terrorists in the network “Wassi†was the focal actor. Based on the PROMETHEE framework, it is resolved that the obtained terrorist nodes can be instrumental for the intelligence and law enforcement agencies to confine their focus on important members of the terrorist network which can deter the functioning of these networks.

  • References

    1. [1] Sarita Azad and Arvind Gupta, “A Quantitative Assessment on 26/11 Mumbai Attack using Social Network Analysis†Journal of Terrorism Research, Volume 2, Issue 2, November 2011. https://doi.org/10.15664/jtr.187.

      [2] M.E.J Newman, Networks: An Introduction, Oxford University Press, 2010. https://doi.org/10.1093/acprof:oso/9780199206650.001.0001.

      [3] M. K. Sparrow. The application of Network Analysis to criminal intelligence: An assessment of the prospects. 1991. Social Networks. Esevier13, 251-274.

      [4] V.E.Krebs. Mapping networks of terrorist cells. 2002. Connections 24(3): 43-52 International Network for Social Network Analysis.

      [5] S. Wasserman and K. Faust. Social Network Analysis: Methods and Applications, Addison-Wesley, 1994. https://doi.org/10.1017/CBO9780511815478.

      [6] Nasrullah Memon, Henrik Legind Larsen, David L. Hicks, and Nicholas Harkiolakis. Detecting Hidden Hierarchy in Terrorist Networks: Some Case Studies. Springer-Verlag, pages 477–489, 2008. Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics.

      [7] Nasrullah Memon, David L. Hicks, and Henrik Legind Larsen. How Investigative Data Mining Can Help Intelligence Agencies to Discover Dependence of Nodes in Terrorist Networks. In Proceedings of the 3rd international conference on Advanced Data Mining and Applications ADMA ’07, pp. 430–441, Berlin, Heidelberg, 2007. Springer-Verlag. https://doi.org/10.1007/978-3-540-73871-8_40.

      [8] Jennifer Xu and Hsinchun Chen. Criminal network analysis and visualization. Commun. Association for Computing Machinery, 48:100–107, June 2005. https://doi.org/10.1145/1064830.1064834.

      [9] Ala Berzinji, Lisa Kaati, Ahmed Resine, Detecting Key Players in Terrorist Networks. European Intelligence and Security Informatics Conference (EISIC), 2012. https://doi.org/10.1109/EISIC.2012.13.

      [10] Brans J.P., Lingenierie de la decision. Elaboration dinstruments daide a la decision. Methode PROMETHEE. In: Nadeau, R., Landry, M. (Eds.), Laide a la decision: Nature, instruments et perspectives davenir, Presses de lUniversite Laval, Quebec, Canada. pp. 183-214, 1982.

      [11] De Keysar, Keyser, W., Peeters, P., A note on the use of PROMETHEE multi criteria methods. European Journal of Operational Research 89, 457–461, 1996. https://doi.org/10.1016/0377-2217(94)00307-6.

      [12] Brans J.P. and Ph. Vincke A preference ranking organization method: The PROMETHEE method. Management Science Vol. 31, 647–656, 1985 https://doi.org/10.1287/mnsc.31.6.647.

      [13] Gilles D’Avignon and Bertrand Mareschal. Specialization of Hospital Services in QUEBEC: An application of the PROMETHEE and GAIA methods. Mathl Cornput. Modelling, Vol. 12, No. 10/l1, pp. 1393-1400, 1989.

      [14] VTomic, Danijel Markovic, Miomir Jovanovic. Application of PROMETHEE method on decision process in mines, International Journal of Engineering, pp. 79-84, 2013.

      [15] Saurabh Singh, Shashikant Verma, Akhilesh Tiwari, Divyani Indurkhya and Aditya Tiwari. An Innovative Investigation on the Importance of Link in Terrorist Network Using Prim’s Algorithm (Anti - Terrorism Approach), In Proceedings of International Conference on Recent Developments in Engineering, Science and Management, 2017.

      [16] Fox, William P., and Sean F. Everton. 2014. "Using Mathematical Models in Decision Making Methodologies to Find Key Nodes in the Noordin Dark Network." American Journal of Operations Research, 4, pp. 255-67. https://doi.org/10.4236/ajor.2014.44025.

      [17] Rahi Gaikwad, Mumbai attackers made two earlier attempts: Headley, The Hindu, February 8, 2016.

      [18] A report on Mumbai attack, “Mumbai terrorist attack (Nov. 26-29, 2008)â€, Govt. of India, 2009.

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    Singh, S., Verma, S., & Tiwari, A. (2018). An innovative approach for identification of pivotal node in terrorist network using promethee method (an anti-terrorism approach). International Journal of Engineering & Technology, 7(1), 95-99. https://doi.org/10.14419/ijet.v7i1.8828