INFORMATION CHANGE THE WORLD

International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.5, No.12, Nov. 2013

Efficient Algorithm for Destabilization of Terrorist Networks

Full Text (PDF, 391KB), PP.21-30


Views:105   Downloads:4

Author(s)

Nisha Chaurasia, Akhilesh Tiwari

Index Terms

Data Mining, Social Network Analysis, Terrorist Network, Graph Theory

Abstract

The advisory feasibility of Social Network Analysis (SNA) to study social networks have encouraged the law enforcement and security agencies to investigate the terrorist network and its behavior along with key players hidden in the web. The study of the terrorist network, utilizing SNA approach and Graph Theory where the network is visualized as a graph, is termed as Investigative Data Mining or in general Terrorist Network Mining. The SNA defined centrality measures have been successfully incorporated in the destabilization of terrorist network by deterring the dominating role(s) from the network. The destabilizing of the terrorist group involves uncovering of network behavior through the defined hierarchy of algorithms. This paper concerning the destabilization of terrorist network proposes a pioneer algorithm which seems to replace the already available hierarchy of algorithms. This paper also suggests use of the two influential centralities, PageRank Centrality and Katz Centrality, for effectively neutralizing of the network.

Cite This Paper

Nisha Chaurasia, Akhilesh Tiwari,"Efficient Algorithm for Destabilization of Terrorist Networks", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.12, pp.21-30, 2013. DOI: 10.5815/ijitcs.2013.12.03

Reference

[1]Jiawei Han & Micheline Kamber: Data Mining: Concepts and Techniques, Second Edition, Morgan Kaufmann Publishers (2006).

[2]Nisha Chaurasia, Mradul Dhakar, Akhilesh Tiwari and R. K. Gupta: A Survey on Terrorist Network Mining: Current Trends and Opportunities, International Journal of Computer Science and Engineering Survey (IJCSES), 3(4), pp. 59 – 66 (2012).

[3]Nasrullah Memon, Henrik Legind Larsen: Structural Analysis and Destabilizing Terrorist Networks, In: The First International Conference on Availability, Reliability and Security, 2006. ARES 2006, IEEE (2006). 

[4]Scott, J.: Social Network Analysis: A Handbook, 2 edn. Sage Publications, London 2000.

[5]Nasrullah Memon, Abdul Rasool Qureshi: Investigative Data Mining and its Application in Counterterrorism, In: Proceedings of the 5th WSEAS Int. Conf. on Applied Informatics and Communications, Malta, pp. 97-403 (2005).

[6]Nasrullah Memon, Kim C. Kristoffersen, David L. Hicks and Henrik Legind Larsen: Detecting Critical Regions in Covert Networks: A Case Study of 9/11 Terrorists Network, In: Second International Conference on Availability, Reliability and Security (ARES'07), IEEE (2007).

[7]Muhammad Akram Shaikh, Wang Jiaxin: Investigative Data Mining: Identifying Key Nodes in Terrorist Networks, Multitopic Conference, 2006. INMIC '06, pp. 201-207 IEEE IEEE (2006).

[8]Uffe Kock Wiil, Nasrullah Memon, and Panagiotis Karampelas: Detecting New Trends in Terrorist Networks: In: 2010 International Conference on Advances in Social Networks Analysis and Mining (2010).

[9]Nasrullah Memon, David L. Hicks and Henrik Legind Larsen: Harvesting Terrorists Information from Web, In: 11th International Conference Information Visualization (IV'07), IEEE (2007).

[10]Nasrullah Memon, Henrik Legind Larsen: Practical Approaches for Analysis, Visualization and Destabilizing Terrorist Networks, In: Proceedings of the First International Conference on Availability, Reliability and Security,ARES (2006).

[11]Nasrullah Memon, David L. Hicks, Dil Muhammad Akbar Hussain and Henrik Legind Larsen: Practical Algorithms And Mathematical Models For Destabilizing Terrorist Networks, In: Sharad Mehrotra, Daniel Dajun Zeng, Hsinchun Chen, Bhavani M. Thuraisingham, Fei-Yue Wang (Eds.): ISI 2006, LNCS 3975, pp. 389. Springer-Verlag Berlin Heidelberg (2006).

[12]Nasrullah Memon, Henrik Legind Larsen, David L. Hicks, and Nicholas Harkiolakis: Detecting Hidden Hierarchy in Terrorist Networks: Some Case Studies, In: Proceedings of Springer-Verlag Berlin Heidelberg 2008, ISI 2008 Workshops, LNCS 5075, pp. 477–489 (2008).

[13]Memon, N., Larsen H.L.: Investigative Data Mining Toolkit: A Software Prototype for Visualizing, Analyzing and Destabilizing Terrorist Networks. In: Visualizing Network Information, pp. 14-1 – 14-24 (2006).

[14]Carley, Kathleen M.; Reminga, Jeffrey; and Kamneva, Natasha: Destabilizing Terrorist Networks, In: Proceedings of the 8th International Command and Control Research and Technology Symposium (2003).

[15]U Kang, Spiros Papadimitriou, Jimeng Sun, Hanghang Tong: Centralities in Large Networks: Algorithms and Observations, In: SIAM International Conference on Data Mining (SDM'2011), Phoenix, U.S.A. (2011).

[16]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 (2011).

[17]Borgatti,. S. P., Everett, M. G. and Freeman, L. C.: UCINET 6 for Windows, Analytic Technologies, Cambridge, MA: Harvard University Press (2002).