Abstract

Prediction of terrorist group using historical data of attacks has been less explored due to the lack of detailed terrorist data which contain terrorist group's attacks and activities. The reasons may be its confidentiality & sensitivity. In this paper we have shown a terrorist group prediction model (TGPM) to predict the terrorist group involved in a given attack. This model initially learns similarities of terrorist incidents from various terrorist attacks to predict the responsible group. The model has been validated with the experimental results. The overall performance of the model shows a fair degree of the accuracy.

References

• David, G. , "Globalization and International Security: Have the Rules of the Game Changed?", In Annual meeting of the International Studies Association, California, USA, http://www. allacademic. com/meta/p98627_index. html, 2006.
• A. Malathi and Dr. S. Santhosh Baboo, "Evolving Data Mining Algorithms on the Prevailing Crime Trend – An Intelligent CrimePrediction Model", In International Journal of Scientific & Engineering Research, June 2011, Vol. 2, Issue 6.
• H. Chen, D. Denning et al. , "The Dark Web Forum Portal: From multi-lingual to video", InIntelligence and Security Informatics (ISI), IEEE conference, 2011.
• Coffman, T. R. , Marcus, S. E. : Pattern Classification in Social Network Analysis: A case study. In: 2004 IEEE Aerospace Conference, March 6-13, 2004.
• Nooy, W. d. , Mrvar, A. , et al. : Exploratory Social Network Analysis with Pajek. Cambridge University Press, New York, 2005.
• Scott, J. : Social Network Analysis. SAGE Publications, London, 2005.
• Wasserman, S. , Faust, K. : Social Network Analysis: Methods and Applications, 1994, pp. 266.
• Faith Ozgul,Zeki Erdem and Chris Bowerman, "Prediction of Unsolved Terrorist Attacks Using Group Detection Algorithms," In LNCS, vol. 5477, pp. 25-30. Springer, Heidelberg, 2009.
• Taipale KA, "Data mining and domestic security: connecting the dots to make sense of data", In Columbia Sci Tech Law Rev 5, 2003, pp. 1–83.
• Ozgul, F. , Bondy, J. , Aksoy, H. : Mining for offender group detection and story of a police operation. In: Sixth Australasian Data Mining Conference (AusDM 2007). Australian Computer Society Conferences in Research and Practice in Information Technology (CRPIT), Gold Coast, Australia , 2007.
• Ozgul, F. , Erdem, Z. , Aksoy, H. : Comparing Two Models for Terrorist Group Detection: GDM or OGDM? In: Yang, C. C. , Chen, H. , Chau, M. , Chang, K. , Lang, S. -D. , Chen, P. S. , Hsieh, R. , Zeng, D. , Wang, F. -Y. , Carley, K. M. , Mao, W. , Zhan, J. (eds. ) ISI Workshops 2008. LNCS, vol. 5075, pp. 149–160. Springer, Heidelberg, 2008.
• Global Terrorism Database, http://www. start. umd. edu/gtd/, Retreived on 05/02/2012.
• South asia terrorism portal , http://www. satp. org/satporgtp/countries/india/terroristoutfits/CPI_M. htm, Retreived on 05/02/2012.
• Dark web portal, "http://cri-portal. dyndns. org/portal/Home. action", Retrieved on 19/02/2012.
• Council on Foreign Relations, http://www. cfr. org/india/terror-groups-india/p12773, Retreived on 05/02/2012.