Abstract
Terrorism, having spread its roots throughout the world, has become a grieve matter of concern globally. In simple words, terrorism is the use of violence to create fear and alarm. Terrorism being a major challenge, the paper deals with how terrorism can be combated using the fastest growing and most effective technology of computer science, i.e. cloud computing. An understanding of the history, nature and mechanism will contribute towards the eradication of terrorism. Here, we will use a directed graph that will provide us with an interconnected network of terrorists’ activities based on the data collected from the Global Terrorism Database (GTD) for a certain period. We will develop an analytical model which would connect the distributed data on terrorists’ activities to aid decision-making by counter-terrorist security agents around the world.
References
Gundabathula, V.T., Vaidhehi, V.: An efficient modelling of terrorist groups in india using machine learning algorithms. Indian J. Sci. Technol. 11(15) (2018)
Goteng, G.L., Tao, X.: Cloud computing intelligent data-driven model: connecting the dots to combat global terrorism. In: 2016 IEEE International Congress on Big Data (BigData Congress), San Francisco, CA, pp. 446–453 (2016)
Talreja, D., Nagaraj, J., Varsha, N.J., Mahesh, K.: Terrorism analytics: learning to predict the perpetrator. In: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, pp. 1723–1726 (2017). https://doi.org/10.1109/icacci.2017.8126092
Mahmood, T., Rohail, K.: Analyzing terrorist events in Pakistan to support counter-terrorism-events, methods and targets. In: 2012 International Conference on Robotics and Artificial Intelligence (ICRAI), pp. 157–164 (2012)
Corner, E., Gill, P., Mason, O.: Mental health disorders and the terrorist: a research note probing selection effects and disorder prevalence. Stud. Conflict Terrorism 39(6), 560–568 (2016)
Perliger, A., Pedahzur, A.: Social network analysis in the study of terrorism and political violence. PS: Polit. Sci. Polit. 44(1), 45–50 (2011)
Gutfraind, A.: Understanding terrorist organizations with a dynamic model. In: Mathematical Methods in Counterterrorism 2009, pp. 107–125. Springer, Vienna
Crenshaw, M.: Current research on terrorism: the academic perspective. Stud. Conflict Terrorism 15(1), 1 (1992)
Krebs, V.E.: Mapping networks of terrorist cells. Connections 24(3), 43–52 (2002)
Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press (1994)
Horgan, J.: From profiles to pathways and roots to routes: perspectives from psychology on radicalization into terrorism. Ann. Am. Acad. Polit. Soc. Sci. 618(1), 80–94 (2008)
Chung, W., Tang, W.: Building a web collection for online surveillance of US domestic terrorism. In: 2012 IEEE International Conference on InIntelligence and Security Informatics (ISI), IEEE, pp. 195–195 (2012)
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Mishra, N., Swagatika, S., Singh, D. (2020). An Intelligent Framework for Analysing Terrorism Actions Using Cloud. In: Patnaik, S., Ip, A., Tavana, M., Jain, V. (eds) New Paradigm in Decision Science and Management. Advances in Intelligent Systems and Computing, vol 1005. Springer, Singapore. https://doi.org/10.1007/978-981-13-9330-3_21
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DOI: https://doi.org/10.1007/978-981-13-9330-3_21
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