A Novel Genetic Based Framework for the Detection and Destabilization of Influencing Nodes in Terrorist Network

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 31)


The Social Network Analysis analyses social network on web. SNA has led the law enforcement agencies to study the behavior of terrorist networks for the identification of relationships that may exist between nodes. Recently, Terrorist Network Mining (special branch of SNA) has been in vogue in Data mining community because of its ability to identify key nodes present in the network. This paper proposes a new approach for Terrorist network mining. The proposed work is carried out in two phases. The first phase proposes Genetic based optimization mechanism. Proposed mechanism is suitable for effective optimization of large social network containing terrorist and non-terrorist nodes. During optimization process removal of non-terrorist nodes from the network has been performed and resultant represents the reduced graph containing only the set of potential nodes. The second phase proposes a weighted degree centrality measure (considers frequency of communication) for effectively neutralizing of the terrorist network.


Social network analysis Terrorist network mining Genetic algorithm 


  1. 1.
    Chaurasia, N., Tiwari, A.: Efficient algorithm for destabilization of terrorist networks. Int. J. Inf. Technol. Comput. Sci. 5(12), 21–30 (2013)Google Scholar
  2. 2.
    Han, J., Kamber, M., Pei, J.: Data Mining : Concepts and Techniques, 3rd edn. Morgan Kaufmann Publications, Massachusetts (2006)Google Scholar
  3. 3.
    Pujari, A.K.: Data Mining Techniques, Universities Press (2001)Google Scholar
  4. 4.
    Maheshwari, S., Tiwari, A.: Genetic Based optimization of social network with special reference to terrorist network mining. TECHNIA-Int. J. Comput. Sci. Commun. Technol. 7:1. [ISSN 0974-3375] (2014)Google Scholar
  5. 5.
    Chaurasia, N., Tiwari, A.: On the use of Brokerage approach to discover influencing nodes in terrorist networks. In: Social Networking, Intelligent Systems Reference Library, vol. 65, pp. 271–295. (doi: 10.1007/978-3-319-05164-2_11) (2014)
  6. 6.
    Marin, A., Wellman, B.: Social network analysis: an introduction. The Sage Handbook of Social Network AnalysisGoogle Scholar
  7. 7.
    Shaikh, M.A., Jiaxin, W.: Investigative data mining: identifying key nodes in terrorist networks (2006)Google Scholar
  8. 8.
    Wasserman, S., Faust, K.: Social Network Analysis, Methods and Applications. Cambridge University Press, Cambridge (1994)CrossRefGoogle Scholar
  9. 9.
    Chaurasia, N., Dhakar, M., Tiwari, A., Gupta, R.K.: A survey on terrorist network mining: currenttrends and opportunities. Int. J. Comput. Sci. Eng. Surv. (IJCSES) 3(4), 59–66 (2012)CrossRefGoogle Scholar
  10. 10.
    Memon, N., Larsen, H.L.: Investigative data mining toolkit: a software prototype for visualizing, analyzing and destabilizing terrorist networks (2006)Google Scholar
  11. 11.
    Memon, N., Hicks, D.L., Hussain, D.M.K., Larsen, H.L.: Practical algorithms and mathematical models for destabilizing terrorist networks. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B.M., Wang, F.-Y. (eds.) ISI 2006, LNCS 3975, pp. 389. Springer-Verlag, Berlin (2006)Google Scholar
  12. 12.
    Memon, N., Larsen, H.L., Hicks, D.L., Harkiolakis, N.: Detecting hidden hierarchy in terrorist networks: some case studies. In: Proceedings of ISI 2008 Workshops, LNCS 5075, pp. 477–489. Springer-Verlag, Berlin (2008)Google Scholar
  13. 13.
    Memon, N., Larsen, H.L.: Practical approaches for analysis, visualization and destabilizing terrorist networks. In: Proceedings of the First International Conference on Availability, Reliability and Security, ARES (2006)Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of CSE and ITMadhav Institute of Technology and ScienceGwaliorIndia

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