Ranking Terrorist Organizations Network in India using Combined Sna-Ahp Approach
Pankaj Choudhary1, Upasna Singh2
1Pankaj Choudhary, Department of Computer Science Engineering, Defence Institute of Advanced Technology Pune (Maharashtra), India.
2Upasna Singh, Department of Computer Science Engineering, Defence Institute of Advanced Technology Pune, India.
Manuscript received on 24 September 2018 | Revised Manuscript received on 30 September 2018 | Manuscript published on 30 November 2018 | PP: 168-172 | Volume-7 Issue-4, November 2018 | Retrieval Number: E1822017519©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Terrorism is one of the major concern Worldwide. Many countries over the globe are developing strategies to fight with terrorism, either kinetically or non-kinetically. Terrorist Networks are often covert in nature, that’s why also called Dark Networks. In this effort, Social Network Analysis (SNA) is a well-known technique among researchers analyzing these Dark Terrorist Networks. Various centrality measures of SNA have been evolved over time for targeting the key players in terrorist or covert networks and finding their ranking. On the other hand, Analytical Hierarchy Process (AHP), a multi-criteria decision making technique, enables subjective as well as objective choices of the decision makers over available criteria and makes decisions over various alternatives. Often, centrality measures of SNA result in different ranking and different set of key players, which makes terrorist targeting very tough. To deal with it, we propose a combined SNA-AHP approach for obtaining the consolidated/final/overall ranking of nodes in various terrorist networks. We consider a case study of a Network of various Terrorist Organizations involved in terrorist activities in India from 2000 to 2003. Final ranking of these terrorist organization is obtained using combined SNA-AHP approach. These rankings are compared with other rankings obtained from existing centrality approaches. To assess the robustness of our approach, sensitivity analysis is proposed and recommended. The results of this study show that the combined SNA-AHP approach delivers promising results in ranking and targeting dark/covert/terrorist networks.
Keywords: Terrorist Network, Analytical Hierarchy Process (AHP), Social Network Analysis (SNA), Centrality Measures, Key Players, Ranking Terrorist Network, Terrorist Targeting, Dark Networks
Scope of the Article: Network Based Applications